research project on statistics

Top 99+ Trending Statistics Research Topics for Students

Being a statistics student, finding the best statistics research topics is quite challenging. But not anymore; find the best statistics research topics now!!!

Statistics is one of the tough subjects because it consists of lots of formulas, equations and many more. Therefore the students need to spend their time to understand these concepts. And when it comes to finding the best statistics research project for their topics, statistics students are always looking for someone to help them.

In this blog, we will share with you the most interesting and trending statistics research topics in 2023. It will not just help you to stand out in your class but also help you to explore more about the world.

If you face any problem regarding statistics, then don’t worry. You can get the best statistics assignment help from one of our experts.

As you know, it is always suggested that you should work on interesting topics. That is why we have mentioned the most interesting research topics for college students and high school students. Here in this blog post, we will share with you the list of 99+ awesome statistics research topics.

Why Do We Need to Have Good Statistics Research Topics?

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Having a good research topic will not just help you score good grades, but it will also allow you to finish your project quickly. Because whenever we work on something interesting, our productivity automatically boosts. Thus, you need not invest lots of time and effort, and you can achieve the best with minimal effort and time.

What Are Some Interesting Research Topics?

If we talk about the interesting research topics in statistics, it can vary from student to student. But here are the key topics that are quite interesting for almost every student:-

Literacy rate in a city.
Abortion and pregnancy rate in the USA.
Eating disorders in the citizens.
Parent role in self-esteem and confidence of the student.
Uses of AI in our daily life to business corporates.

Top 99+ Trending Statistics Research Topics For 2023

Here in this section, we will tell you more than 99 trending statistics research topics:

Sports Statistics Research Topics

Statistical analysis for legs and head injuries in Football.
Statistical analysis for shoulder and knee injuries in MotoGP.
Deep statistical evaluation for the doping test in sports from the past decade.
Statistical observation on the performance of athletes in the last Olympics.
Role and effect of sports in the life of the student.

Psychology Research Topics for Statistics

Deep statistical analysis of the effect of obesity on the student’s mental health in high school and college students.
Statistical evolution to find out the suicide reason among students and adults.
Statistics analysis to find out the effect of divorce on children in a country.
Psychology affects women because of the gender gap in specific country areas.
Statistics analysis to find out the cause of online bullying in students’ lives.
In Psychology, PTSD and descriptive tendencies are discussed.
The function of researchers in statistical testing and probability.
Acceptable significance and probability thresholds in clinical Psychology.
The utilization of hypothesis and the role of P 0.05 for improved comprehension.
What types of statistical data are typically rejected in psychology?
The application of basic statistical principles and reasoning in psychological analysis.
The role of correlation is when several psychological concepts are at risk.
Actual case study learning and modeling are used to generate statistical reports.
In psychology, naturalistic observation is used as a research sample.
How should descriptive statistics be used to represent behavioral data sets?

Applied Statistics Research Topics

Does education have a deep impact on the financial success of an individual?
The investment in digital technology is having a meaningful return for corporations?
The gap of financial wealth between rich and poor in the USA.
A statistical approach to identify the effects of high-frequency trading in financial markets.
Statistics analysis to determine the impact of the multi-agent model in financial markets.

Personalized Medicine Statistics Research Topics

Statistical analysis on the effect of methamphetamine on substance abusers.
Deep research on the impact of the Corona vaccine on the Omnicrone variant.
Find out the best cancer treatment approach between orthodox therapies and alternative therapies.
Statistics analysis to identify the role of genes in the child’s overall immunity.
What factors help the patients to survive from Coronavirus .

Experimental Design Statistics Research Topics

Generic vs private education is one of the best for the students and has better financial return.
Psychology vs physiology: which leads the person not to quit their addictions?
Effect of breastmilk vs packed milk on the infant child overall development
Which causes more accidents: male alcoholics vs female alcoholics.
What causes the student not to reveal the cyberbullying in front of their parents in most cases.

Easy Statistics Research Topics

Application of statistics in the world of data science
Statistics for finance: how statistics is helping the company to grow their finance
Advantages and disadvantages of Radar chart
Minor marriages in south-east Asia and African countries.
Discussion of ANOVA and correlation.
What statistical methods are most effective for active sports?
When measuring the correctness of college tests, a ranking statistical approach is used.
Statistics play an important role in Data Mining operations.
The practical application of heat estimation in engineering fields.
In the field of speech recognition, statistical analysis is used.
Estimating probiotics: how much time is necessary for an accurate statistical sample?
How will the United States population grow in the next twenty years?
The legislation and statistical reports deal with contentious issues.
The application of empirical entropy approaches with online grammar checking.
Transparency in statistical methodology and the reporting system of the United States Census Bureau.

Statistical Research Topics for High School

Uses of statistics in chemometrics
Statistics in business analytics and business intelligence
Importance of statistics in physics.
Deep discussion about multivariate statistics
Uses of Statistics in machine learning

Survey Topics for Statistics

Gather the data of the most qualified professionals in a specific area.
Survey the time wasted by the students in watching Tvs or Netflix.
Have a survey the fully vaccinated people in the USA
Gather information on the effect of a government survey on the life of citizens
Survey to identify the English speakers in the world.

Statistics Research Paper Topics for Graduates

Have a deep decision of Bayes theorems
Discuss the Bayesian hierarchical models
Analysis of the process of Japanese restaurants.
Deep analysis of Lévy’s continuity theorem
Analysis of the principle of maximum entropy

AP Statistics Topics

Discuss about the importance of econometrics
Analyze the pros and cons of Probit Model
Types of probability models and their uses
Deep discussion of ortho stochastic matrix
Find out the ways to get an adjacency matrix quickly

Good Statistics Research Topics

National income and the regulation of cryptocurrency.
The benefits and drawbacks of regression analysis.
How can estimate methods be used to correct statistical differences?
Mathematical prediction models vs observation tactics.
In sociology research, there is bias in quantitative data analysis.
Inferential analytical approaches vs. descriptive statistics.
How reliable are AI-based methods in statistical analysis?
The internet news reporting and the fluctuations: statistics reports.
The importance of estimate in modeled statistics and artificial sampling.

Business Statistics Topics

Role of statistics in business in 2023
Importance of business statistics and analytics
What is the role of central tendency and dispersion in statistics
Best process of sampling business data.
Importance of statistics in big data.
The characteristics of business data sampling: benefits and cons of software solutions.
How may two different business tasks be tackled concurrently using linear regression analysis?
In economic data relations, index numbers, random probability, and correctness are all important.
The advantages of a dataset approach to statistics in programming statistics.
Commercial statistics: how should the data be prepared for maximum accuracy?

Statistical Research Topics for College Students

Evaluate the role of John Tukey’s contribution to statistics.
The role of statistics to improve ADHD treatment.
The uses and timeline of probability in statistics.
Deep analysis of Gertrude Cox’s experimental design in statistics.
Discuss about Florence Nightingale in statistics.
What sorts of music do college students prefer?
The Main Effect of Different Subjects on Student Performance.
The Importance of Analytics in Statistics Research.
The Influence of a Better Student in Class.
Do extracurricular activities help in the transformation of personalities?
Backbenchers’ Impact on Class Performance.
Medication’s Importance in Class Performance.
Are e-books better than traditional books?
Choosing aspects of a subject in college

How To Write Good Statistics Research Topics?

So, the main question that arises here is how you can write good statistics research topics. The trick is understanding the methodology that is used to collect and interpret statistical data. However, if you are trying to pick any topic for your statistics project, you must think about it before going any further.

As a result, it will teach you about the data types that will be researched because the sample will be chosen correctly. On the other hand, your basic outline for choosing the correct topics is as follows:

Introduction of a problem
Methodology explanation and choice.
Statistical research itself is in the main part (Body Part).
Samples deviations and variables.
Lastly, statistical interpretation is your last part (conclusion).

Note: Always include the sources from which you obtained the statistics data.

Top 3 Tips to Choose Good Statistics Research Topics

It can be quite easy for some students to pick a good statistics research topic without the help of an essay writer. But we know that it is not a common scenario for every student. That is why we will mention some of the best tips that will help you choose good statistics research topics for your next project. Either you are in a hurry or have enough time to explore. These tips will help you in every scenario.

1. Narrow down your research topic

We all start with many topics as we are not sure about our specific interests or niche. The initial step to picking up a good research topic for college or school students is to narrow down the research topic.

For this, you need to categorize the matter first. And then pick a specific category as per your interest. After that, brainstorm about the topic’s content and how you can make the points catchy, focused, directional, clear, and specific.

2. Choose a topic that gives you curiosity

After categorizing the statistics research topics, it is time to pick one from the category. Don’t pick the most common topic because it will not help your grades and knowledge. Instead of it, please choose the best one, in which you have little information, or you are more likely to explore it.

In a statistics research paper, you always can explore something beyond your studies. By doing this, you will be more energetic to work on this project. And you will also feel glad to get them lots of information you were willing to have but didn’t get because of any reasons.

It will also make your professor happy to see your work. Ultimately it will affect your grades with a positive attitude.

3. Choose a manageable topic

Now you have decided on the topic, but you need to make sure that your research topic should be manageable. You will have limited time and resources to complete your project if you pick one of the deep statistics research topics with massive information.

Then you will struggle at the last moment and most probably not going to finish your project on time. Therefore, spend enough time exploring the topic and have a good idea about the time duration and resources you will use for the project.

Statistics research topics are massive in numbers. Because statistics operations can be performed on anything from our psychology to our fitness. Therefore there are lots more statistics research topics to explore. But if you are not finding it challenging, then you can take the help of our statistics experts . They will help you to pick the most interesting and trending statistics research topics for your projects.

With this help, you can also save your precious time to invest it in something else. You can also come up with a plethora of topics of your choice and we will help you to pick the best one among them. Apart from that, if you are working on a project and you are not sure whether that is the topic that excites you to work on it or not. Then we can also help you to clear all your doubts on the statistics research topic.

Frequently Asked Questions

Q1. what are some good topics for the statistics project.

Have a look at some good topics for statistics projects:- 1. Research the average height and physics of basketball players. 2. Birth and death rate in a specific city or country. 3. Study on the obesity rate of children and adults in the USA. 4. The growth rate of China in the past few years 5. Major causes of injury in Football

Q2. What are the topics in statistics?

Statistics has lots of topics. It is hard to cover all of them in a short answer. But here are the major ones: conditional probability, variance, random variable, probability distributions, common discrete, and many more.

Q3. What are the top 10 research topics?

Here are the top 10 research topics that you can try in 2023:

1. Plant Science 2. Mental health 3. Nutritional Immunology 4. Mood disorders 5. Aging brains 6. Infectious disease 7. Music therapy 8. Political misinformation 9. Canine Connection 10. Sustainable agriculture

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120 Statistical Research Topics: Explore Up-to-date Trends

Statistical Research Topics Latest Trends & Techniques

Researchers and statistics teachers are often tasked with writing an article or paper on a given stats project idea. One of the most crucial things in writing an outstanding and well-composed statistics research project, paper, or essay is to come up with a very interesting topic that will captivate your reader’s minds and provoke their thoughts.

What Are the Best Statistical Research Topics Worth Writing On?

Leading statistical research topics for college students that will interest you, project topics in statistics worth considering, the best idea for statistics project you can focus on, good experiments for statistics topics you should be writing on, what are the best ap statistics project ideas that will be of keen interest to you, good statistics project ideas suitable for our modern world, some of the most crucial survey topics for statistics project, statistical projects topics every researcher wants to write on, statistical research topics you can focus your research on.

Students often find it difficult to come up with well-composed statistical research project topics that take the format of argumentative essay topics to pass across their message. In this essay, we will look at some of the most interesting statistics research topics to focus your research on.

Here are some of the best statistical research topics worth writing on:

Predictive Healthcare Modeling with Machine Learning
Analyzing Online Education During COVID-19 Epidemic
Modeling How Climate Change Affects Natural Disasters
Essential Elements Influencing Personnel Productivity
Social Media Influence on Customer Choices and Behavior
Can Geographical Statistics Aid In Analyzing Crime Trends and Patterns?
Financial Markets and Stock Price Predictions
Statistical Analysis of Voting-related Behaviors
An Analysis of Public Transportation Usage Trends in Urban Areas
How Can Public Health Education Reduce Air Pollution?
Statistical Analysis of Suicide In Adolescents and Adults
A Review of Divorce and How It Affects Children

As a college student, here are the best statistical projects for high school students to focus your research on, especially if you need social media research topics .

Major Factors Influencing College Students’ Academic Performance
Social Media and How It Defines thee Mental Health of Students
Evaluation of the Elements Influencing Student Engagement and Retention
An Examination of Extracurricular Activities On Academic Success
Does Parental Involvement Determine Academic Achievement of Kids?
Examining How Technology Affects Improving Educational Performance
Factors That Motivate Students’ Involvement In Online Learning
The Impact of Socioeconomic Status On Academic Performance
Does Criticism Enhance Student Performance?
Student-Centered Learning and Improved Performance
A Cursory Look At Students’ Career Goals and Major Life Decisions
Does Mental Health Impact Academic Achievement?

Are you a student tasked with writing a project but can’t come up with befitting stats research topics? Here are the best ideas for statistical projects worth considering:

Financial Data And Stock Price Forecasting
Investigation of Variables Influencing Students’ Grades
What Causes Traffic Flow and Congestion In Urban Areas?
How to Guarantee Customer Retention In the Retail Sector
Using Epidemiological Data to Model the Spread of Infectious Diseases
Does Direct Advertisement Affect Consumer Preferences and Behavior?
How to Predict and Adapt to Climate Change
Using Spatial Statistics to Analyze Trends and Patterns In Crime
Examination of the Elements Influencing Workplace Morale and Productivity
Understanding User Behavior and Preferences Through Statistical Analysis of Social Media Data
How Many Percent Get Married After Their Degree Programs?
A Comparative Analysis of Different Academic Fee Payments

If you have been confused based on the availability of different statistics project topics to choose from, here are some of the best thesis statement about social media to choose from:

Analysis of the Variables Affecting A Startup’s Success
The Valid Connection Between Mental Health and Social Media Use
Different Teaching Strategies and Academic Performance
Factors Influencing Employee Satisfaction In Different Work Environments
The Impact of Public Policy On Different Population Groups
Reviewing Different Health Outcomes and Incomes
Different Marketing Tactics for Good Service Promotion
What Influences Results In Different Sports Competitions?
Differentiating Elements Affecting Students’ Performance In A Given Subject
Internal Communication and Building An Effective Workplace
Does the Use of Business Technologies Boost Workers’ Output?
The Role of Modern Communication In An Effective Company Management

Are you a student tasked with writing an essay on social issues research topics but having challenges coming up with a topic? Here are some amazing statistical experiments ideas you can center your research on.

How Global Pandemic Affects Local Businesses
Investigating the Link Between Income and Health Outcomes In a Demography
Key Motivators for Student’s Performance In a Particular Academic Program
Evaluating the Success of a Promotional Plan Over Others
Continuous Social Media Use and Impact On Mental Health
Does Culture Impact the Religious Beliefs of Certain Groups?
Key Indicators of War and How to Manage These Indicators
An Overview of War As a Money Laundering Scheme
How Implementations Guarantee Effectiveness of Laws In Rural Areas
Performance of Students In War-torn Areas
Key Indicators For Measuring the Success of Your Venture
How Providing FAQs Can Help a Business Scale

The best AP statistic project ideas every student especially those interested in research topics for STEM students will want to write in include:

The Most Affected Age Demography By the Covid-19 Pandemic
The Health Outcomes Peculiar to a Specific Demography
Unusual Ways to Enhance Student Performance In a Classroom
How Marketing Efforts Can Determine Promotional Outputs
Can Mental Health Solutions Be Provided On Social Media?
Assessing How Certain Species Are Affected By Climate Change.
What Influences Voter Turnouts In Different Elections?
How Many People Have Used Physical Exercises to Improve Mental Health
How Financial Circumstances Can Determine Criminal Activities
Ways DUI Laws Can Reduce Road Accidents
Examining the Connection Between Corruption and Underdevelopment In Africa
What Key Elements Do Top Global Firms Engage for Success?

If you need some of the best economics research paper topics , here are the best statistics experiment ideas you can write research on:

Retail Client Behaviors and Weather Trends
The Impact of Marketing Initiatives On Sales and Customer Retention
How Socioeconomic Factors Determine Crime Rates In Different Locations
Public and Private School Students: Who Performs Better?
How Fitness Affects the Mental Health of People In Different Ages
Focus On the Unbanked Employees Globally
Does Getting Involve In a Kid’s Life Make Them Better?
Dietary Decisions and a Healthy Life
Managing Diabetes and High Blood Pressure of a Specific Group
How to Engage Different Learning Methods for Effectiveness
Understudying the Sleeping Habits of Specific Age Groups
How the Numbers Can Help You Create a Brand Recognition

As a student who needs fresh ideas relating to the topic for a statistics project to write on, here are crucial survey topics for statistics that will interest you.

Understanding Consumer Spending and Behavior In Different Regions
Why Some People in Certain Areas Live Longer than Others
Comparative Analysis of Different Customer Behaviors
Do Social Media Businesses Benefit More than Physical Businesses?
Does a Healthy Work Environment Guarantee Productivity?
The Impact of Ethnicity and Religion On Voting Patterns
Does Financial Literacy Guarantee Better Money Management?
Cultural Identities and Behavioral Patterns
How Religious Orientation Determines Social Media Use
The Growing Need for Economists Globally
Getting Started with Businesses On Social Media
Which Is Better: A 9-5 or An Entrepreneurial Job?

Do you want to write on unique statistical experiment ideas? Here are some topics you do not want to miss out on:

Consumer Satisfaction-Related Variables on E-Commerce Websites
Obesity Rates and Socioeconomic Status In Developed Countries
How Marketing Strategies Can Make or Mar Sales Performance
The Correlation Between Increased Income and Happiness In Various Nations
Regression Models and Forecasting Home Prices
Climate Change Affecting Agricultural Production In Specific Areas
A Study of Employee Satisfaction In the Healthcare Industry
Social Media, Marketing Tactics, and Consumer Behavior In the Fashion Industry
Predicting the Risk of Default Among Credit Card Holders In Different Regions
Why Crime Rates Are Increasing In Urban Areas than Rural Areas
Statistical Evaluation of Methamphetamine’s Impact On Drug Users
Genes and a Child’s Total Immunity

Here are some of the most carefully selected stat research topics you can focus on.

Social Media’s Effects On Consumer Behavior
The Correlation Between Urban Crime Rates and Poverty Levels
Physical Exercise and Mental Health Consequences
Predictive Modeling In the Financial Markets
How Minimum Wage Regulations Impact Employment Rates
Healthcare Outcomes and Access Across Various Socioeconomic Groups
How High School Students’ Environment Affect Academic Performance
Automated Technology and Employment Loss
Environmental Elements and Their Effects On Public Health
Various Advertising Tactics and How They Influence Customer Behavior
Political Polarization And Economic Inequality
Climate Change and Agricultural Productivity

The above statistics final project examples will stimulate your curiosity and test your abilities, and they can even be linked to some biochemistry topics and anatomy research paper topics . Writing about these statistics project ideas helps provide a deeper grasp of the natural and social phenomena that affect our lives and the environment by studying these subjects.

Effective Use of Statistics in Research – Methods and Tools for Data Analysis

Remember that impending feeling you get when you are asked to analyze your data! Now that you have all the required raw data, you need to statistically prove your hypothesis. Representing your numerical data as part of statistics in research will also help in breaking the stereotype of being a biology student who can’t do math.

Statistical methods are essential for scientific research. In fact, statistical methods dominate the scientific research as they include planning, designing, collecting data, analyzing, drawing meaningful interpretation and reporting of research findings. Furthermore, the results acquired from research project are meaningless raw data unless analyzed with statistical tools. Therefore, determining statistics in research is of utmost necessity to justify research findings. In this article, we will discuss how using statistical methods for biology could help draw meaningful conclusion to analyze biological studies.

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Role of Statistics in Biological Research

Statistics is a branch of science that deals with collection, organization and analysis of data from the sample to the whole population. Moreover, it aids in designing a study more meticulously and also give a logical reasoning in concluding the hypothesis. Furthermore, biology study focuses on study of living organisms and their complex living pathways, which are very dynamic and cannot be explained with logical reasoning. However, statistics is more complex a field of study that defines and explains study patterns based on the sample sizes used. To be precise, statistics provides a trend in the conducted study.

Biological researchers often disregard the use of statistics in their research planning, and mainly use statistical tools at the end of their experiment. Therefore, giving rise to a complicated set of results which are not easily analyzed from statistical tools in research. Statistics in research can help a researcher approach the study in a stepwise manner, wherein the statistical analysis in research follows –

1. Establishing a Sample Size

Usually, a biological experiment starts with choosing samples and selecting the right number of repetitive experiments. Statistics in research deals with basics in statistics that provides statistical randomness and law of using large samples. Statistics teaches how choosing a sample size from a random large pool of sample helps extrapolate statistical findings and reduce experimental bias and errors.

2. Testing of Hypothesis

When conducting a statistical study with large sample pool, biological researchers must make sure that a conclusion is statistically significant. To achieve this, a researcher must create a hypothesis before examining the distribution of data. Furthermore, statistics in research helps interpret the data clustered near the mean of distributed data or spread across the distribution. These trends help analyze the sample and signify the hypothesis.

3. Data Interpretation Through Analysis

When dealing with large data, statistics in research assist in data analysis. This helps researchers to draw an effective conclusion from their experiment and observations. Concluding the study manually or from visual observation may give erroneous results; therefore, thorough statistical analysis will take into consideration all the other statistical measures and variance in the sample to provide a detailed interpretation of the data. Therefore, researchers produce a detailed and important data to support the conclusion.

Types of Statistical Research Methods That Aid in Data Analysis

Statistical analysis is the process of analyzing samples of data into patterns or trends that help researchers anticipate situations and make appropriate research conclusions. Based on the type of data, statistical analyses are of the following type:

1. Descriptive Analysis

The descriptive statistical analysis allows organizing and summarizing the large data into graphs and tables . Descriptive analysis involves various processes such as tabulation, measure of central tendency, measure of dispersion or variance, skewness measurements etc.

2. Inferential Analysis

The inferential statistical analysis allows to extrapolate the data acquired from a small sample size to the complete population. This analysis helps draw conclusions and make decisions about the whole population on the basis of sample data. It is a highly recommended statistical method for research projects that work with smaller sample size and meaning to extrapolate conclusion for large population.

3. Predictive Analysis

Predictive analysis is used to make a prediction of future events. This analysis is approached by marketing companies, insurance organizations, online service providers, data-driven marketing, and financial corporations.

4. Prescriptive Analysis

Prescriptive analysis examines data to find out what can be done next. It is widely used in business analysis for finding out the best possible outcome for a situation. It is nearly related to descriptive and predictive analysis. However, prescriptive analysis deals with giving appropriate suggestions among the available preferences.

5. Exploratory Data Analysis

EDA is generally the first step of the data analysis process that is conducted before performing any other statistical analysis technique. It completely focuses on analyzing patterns in the data to recognize potential relationships. EDA is used to discover unknown associations within data, inspect missing data from collected data and obtain maximum insights.

6. Causal Analysis

Causal analysis assists in understanding and determining the reasons behind “why” things happen in a certain way, as they appear. This analysis helps identify root cause of failures or simply find the basic reason why something could happen. For example, causal analysis is used to understand what will happen to the provided variable if another variable changes.

7. Mechanistic Analysis

This is a least common type of statistical analysis. The mechanistic analysis is used in the process of big data analytics and biological science. It uses the concept of understanding individual changes in variables that cause changes in other variables correspondingly while excluding external influences.

Important Statistical Tools In Research

Researchers in the biological field find statistical analysis in research as the scariest aspect of completing research. However, statistical tools in research can help researchers understand what to do with data and how to interpret the results, making this process as easy as possible.

1. Statistical Package for Social Science (SPSS)

It is a widely used software package for human behavior research. SPSS can compile descriptive statistics, as well as graphical depictions of result. Moreover, it includes the option to create scripts that automate analysis or carry out more advanced statistical processing.

2. R Foundation for Statistical Computing

This software package is used among human behavior research and other fields. R is a powerful tool and has a steep learning curve. However, it requires a certain level of coding. Furthermore, it comes with an active community that is engaged in building and enhancing the software and the associated plugins.

3. MATLAB (The Mathworks)

It is an analytical platform and a programming language. Researchers and engineers use this software and create their own code and help answer their research question. While MatLab can be a difficult tool to use for novices, it offers flexibility in terms of what the researcher needs.

4. Microsoft Excel

Not the best solution for statistical analysis in research, but MS Excel offers wide variety of tools for data visualization and simple statistics. It is easy to generate summary and customizable graphs and figures. MS Excel is the most accessible option for those wanting to start with statistics.

5. Statistical Analysis Software (SAS)

It is a statistical platform used in business, healthcare, and human behavior research alike. It can carry out advanced analyzes and produce publication-worthy figures, tables and charts .

6. GraphPad Prism

It is a premium software that is primarily used among biology researchers. But, it offers a range of variety to be used in various other fields. Similar to SPSS, GraphPad gives scripting option to automate analyses to carry out complex statistical calculations.

This software offers basic as well as advanced statistical tools for data analysis. However, similar to GraphPad and SPSS, minitab needs command over coding and can offer automated analyses.

Use of Statistical Tools In Research and Data Analysis

Statistical tools manage the large data. Many biological studies use large data to analyze the trends and patterns in studies. Therefore, using statistical tools becomes essential, as they manage the large data sets, making data processing more convenient.

Following these steps will help biological researchers to showcase the statistics in research in detail, and develop accurate hypothesis and use correct tools for it.

There are a range of statistical tools in research which can help researchers manage their research data and improve the outcome of their research by better interpretation of data. You could use statistics in research by understanding the research question, knowledge of statistics and your personal experience in coding.

Have you faced challenges while using statistics in research? How did you manage it? Did you use any of the statistical tools to help you with your research data? Do write to us or comment below!

Frequently Asked Questions

Statistics in research can help a researcher approach the study in a stepwise manner: 1. Establishing a sample size 2. Testing of hypothesis 3. Data interpretation through analysis

Statistical tools in research can help researchers understand what to do with data and how to interpret the results, making this process as easy as possible. They can manage large data sets, making data processing more convenient. A great number of tools are available to carry out statistical analysis of data like SPSS, SAS (Statistical Analysis Software), and Minitab.

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145 Best Statistics Project Ideas and Topics To Consider

Table of Contents

Are you a statistics student hunting for the best research project ideas? If yes, then this blog post is for you. Basically, statistics is a wide academic discipline that studies data and numerical information in almost all fields and various real-life situations that are related to mathematical science. Since the subject is broad, it might be extremely challenging to brainstorm and identify a good statistics research project topic. Therefore, to make your topic selection process easier, here, we have compiled a list of top statistics project ideas for you to consider. Explore them all and pick any idea that meets your requirements.

List of Statistics Project Ideas

For writing an exclusive statistics research paper, you can choose any of the below-mentioned statistics project ideas that justify your knowledge and understanding.

Statistics Project Ideas for School and College Students

Increasing use of plastics
Statistical analysis of the road accidents in your local area
Course cost differentiation in colleges
Are college students likely to develop drug addictions if given a chance?
Are online classes helpful?
Time spent by college students on social media
Significance of the front seats in the class on success rates
The effects of sitting in the backseat in a class
Should mobile phones be allowed in high school or not?
The ratio of college students getting married after graduation
Relation between birth order as well as success in academics
Is being headstrong difficult, or does it make things easy?
Popular movie genre among students in college
Web browsing habits of college students
Caffeine consumption among students as well as its effect on the performance
Common subjects were chosen by students in college
What types of music do college students like the most?
Are e-books better than conventional books?
Choosing aspects of a subject in college
Do extra-curricular activities help transform personalities?
Should stereotypical social issues be highlighted or not?
Comparison between male as well as female students in college
Comparative study on the pricing of different clothing store prices in your town.
Does the race of actors affect the popularity of TV shows among college students?
Does the experience of a freshman in college with their roommate affect their overall experience at the institution?
Does the effect of a Teacher who is fresher in University influence the student’s performance?
Influence of Distinct Subjects on Student’s Performance.
Significance of Analytics in Studying Statistics.
Influence of Better Student in Class
Influence of Backbenchers in their Performance in Class.
Significance of Medication in Class Performance

Business Statistics Project Ideas

Accessibility of businesses to bank benefits
The influence of social media on business sales
The effect of social media on the performance of an employee
Is consumption of alcohol higher among employees with a lower pay scale?
The impact of cost estimation on business management
Sexual harassment amongst female employees in the workplace
Factors contributing to low productivity in a workplace
Consideration of occupational schedules provided by secretaries
Trends of death management in business entities
Relationship between the leaders of a company as well as its employees
The utilization of modern tools in any organization
The effect of modern communication on the management of a company
The importance of internal communication in a workplace
Can business tools improve the performance of employees?
The significance of assessment analysis.
Correlation of business venture investment in the United States.
Importance of online Business Performance for the impaired workers.
Impact of the Facebook Marketing on Business Sales.
Influence of Supervisors on the CEO of Business.

Statistics Project Ideas on Socio-Economics

Significance of agricultural loans for farmers
Comparison between criminal offenses in town as well as villages
The effect of poverty on crime rates
Food habits in low-income families
Malpractices of low-income groups
Income versus explanation analysis in a society
Peak traffic times in your city
Analysis of road accidents in the suburb as well as the town area
The effect of smoking on medical costs
Analysis of the source of revenue as well as the pattern of expenditure by the local government of the local government
A relationship between exercises as well as a reduction in overall medical expenses
The impact of per capita income on healthcare cost
The reason behind drastic development in any city
Comparison and relation between petroleum prices with food prices
Why is it important to train the youth of low-income families?

Statistics Project Topics on Finance and Economics

Can the growth of an organization in society make a difference in the economy of that community?
Performance analysis of the banking sector
Factors affecting financial distress in the banking sector
Do federal elections affect stock prices?
Do debt reduction policies of the government also reduce the quality of life?
Analysis of cash deposit patterns in banks.
Are computerized budget analysis systems effective?
Statistical analysis of the impact of birth and death rates on the economy of a country
Statistical analysis of infant mortality rate.
Is there a relationship between exercise and a reduction in overall medical costs?
The effects of poor infrastructural facilities on socio-economic development.
Are members of certain subpopulations more likely to get the death penalty?
Analysis of the use of financial reports in assessing the performance of banks.
Analysis of the sources of revenue and the pattern of expenditure of the local government.
Regression analysis on national income.
Income vs Consumption Explanation Study in the Society.
Influence of Advertisement on Health Costs
Study of the Worldwide economic growth.
Influence of Pandemic on Health in the UK

Statistical Analysis Topics on Sports and Movies

Is there a relation between a basketball player as well as his height?
Do sports affect the behavior of an individual?
Do students get lower grades if they are involved in college sports?
Comparison between hockey as well as basketball?
Types of shoes worn by basketball players
Are energy drinks harmful?
The popularity of baseball as well as football
Is the involvement of students in sports the reason behind lower grades?
Statistical analysis of the types of brands endorsed by celebrity sportsmen.
The revolution of cinema
Why is there a demand for movie stars?
Does the cast of a movie influence the interest of people?
Do people enjoy movies more while eating?
Do people enjoy movies more when they eat popcorn?
What are the aspects of a successful movie?
What are the qualities of a great movie?
Do People enjoy commercials vs Art Movies?
Do People in the East like Cricket more than People like Football in the West?
Is Sports or Movies More Enjoyable?

Interesting Statistics Project Topics

Examine the connection between mental health outcomes and social media usage.
Examine the factors that influence voter participation in a particular election or region.
Determine whether a particular marketing promotion strategy is working.
Examine a specific species’ response to climate change.
Analyze the connection between mental health outcomes and exercise.
Examine the connection between a particular area’s health outcomes and income.
Determine whether a particular program or intervention is successful in addressing a particular social problem.
Examine the impact that COVID-19 has had on a particular sector of the economy or industry.
Research the connection between a region’s economic conditions and crime rates.
Investigate the factors that influence a student’s success in a specific academic program.

Statistics Project Ideas for College Assignments

Determine whether there is a correlation between having a part-time job and grades.
Analyze whether there is a correlation between student debt and grades.
Examine the GPAs of students who are from out of state to those who are inside the state.
Determine whether there is a correlation between religious affiliation and grades.
Analyze the academic performance of students who have completed an internship.
Compare the test scores for students who have to work to support themselves vs. those who do not have to work.
Analyze the GPAs of students who are married to those who are not married.
Compare the efficiency of different study methods.
Compare the test scores of African American students to Caucasian students.
Investigate the correlation between intelligence and grades.

Final Words

Out of the wide list of statistics project ideas suggested in this blog post, you can pick the topic of your choice. During the topic selection, keep in mind that the topic you select should have enough data to organize, analyze and interpret. Never pick a project idea that falls out of your interest. In case the topic you have selected is vague, then you can’t write a good hypothesis, and also it may result in low grades. So, spend some time and choose the best statistic project idea that is thought-provoking.

In case, you have no idea what topic to choose for your statistic project or if you need expert help to complete your statistics research project, contact us quickly. On our platform, we have numerous statistics assignments help experts to do your project according to the requirements you share with us. Most importantly, by utilizing our statistics and Strategic Management Assignment Help service, you can also finish your tasks ahead of the deadline and achieve an A+ grade.

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101 Statistics Project Ideas For School And College Students

Welcome to the world of statistics, where numbers help us discover interesting things about our daily lives. In this blog, we’re going on a journey exploring “Statistics Project Ideas.” Statistics is more than just working with numbers; it’s like a handy tool to uncover the stories around us. We will examine simple, exciting project ideas that let you dive into real-life situations.

We’ll check out things like study habits and the mysteries of social media trends. Whether you’re a student searching for a cool project or just curious about what data can tell us, join us as we make understanding statistics fun and easy with Statistics Project Ideas. Let’s tell stories with numbers!

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What Is a Statistical Project?

Table of Contents

A statistical project involves using numbers and data to answer questions about the world. It’s like solving real-life puzzles by collecting, analyzing, and interpreting information. For example, you might study how study hours relate to exam grades or explore the distribution of ages in a group.

These projects help us understand patterns, make predictions, and draw conclusions. Whether it’s in school, analyzing sports data, or studying health trends, statistical projects are a way to explore and learn about the world through the lens of numbers and information.

101 Exciting Statistics Project Ideas

Here are some Statistics Project Ideas for students.

Descriptive Statistics Projects

Analyzing the distribution of student grades in a class.
Investigating the average daily temperature in a specific location over a month.
Examining the distribution of income levels in a given population.
Analyzing the frequency of different types of crimes in a city.
Studying the distribution of ages in a sample population.

Inferential Statistics Projects

Testing whether two study groups have a significant difference in exam scores.
Investigating if there is a correlation between hours of study and exam performance.
Exploring the impact of a new teaching method on student achievement.
Testing the hypothesis that there is a gender-based preference for certain academic subjects.
Investigating the relationship between smoking habits and lung capacity.

Also Read:- Social Studies Fair Project Ideas

Regression Analysis Projects

Anticipating the sales of a product based on advertising expenditure.
Analyzing the relationship between the number of hours spent on homework and GPA.
Forecasting the performance of athletes based on their training hours.
Examining the correlation between car speed and fuel efficiency.
Investigating the relationship between sleep duration & cognitive performance.

Survey Design and Analysis Projects

Surveying to analyze the most popular social media platforms among students.
Investigating public opinion on a controversial social or political issue.
Analyzing consumer preferences for a specific product through a survey.
Studying the factors influencing college students’ choice of majors.
Examining the correlation between job satisfaction and employee engagement.

Biostatistics Projects

Exploring the efficacy of a new drug in a clinical trial.
Investigating the prevalence of a specific disease in different age groups.
Studying the impact of a health intervention on a population’s well-being.
Analyzing the correlation between diet and weight loss in a sample population.
Investigating the distribution of body mass index (BMI) in a specific demographic.

Sports Statistics Projects

Analyzing the performance of teams in a sports league over multiple seasons.
Investigating the impact of player injuries on team success in a sports league.
Analyzing the correlation between player statistics and team performance.
Studying the effectiveness of different coaching strategies in a sports team.
Investigating the factors influencing the outcome of penalty shootouts in soccer.

Economics and Finance Projects

Exploring the impact of interest rates on consumer spending.
Investigating the correlation between unemployment rates and stock market performance.
Studying the relationship between inflation and purchasing power.
Analyzing the factors influencing housing prices in a specific region.
Investigating the impact of government policies on economic growth.

Environmental Statistics Projects

Analyzing the distribution of air quality index (AQI) in a city.
Investigating the correlation between deforestation and wildlife population decline.
Exploring the effect of climate change on sea levels in a specific region.
Analyzing the distribution of plastic waste in different water bodies.
Investigating the effectiveness of recycling programs in reducing environmental impact.

Also Read:- Agriscience Fair Project Ideas

Technology and IT Projects

Analyzing the correlation between website loading times and user engagement.
Investigating the distribution of software usage across different industries.
Studying the effectiveness of cybersecurity measures in preventing data breaches.
Analyzing the correlation between app ratings and user reviews.
Investigating the factors influencing smartphone adoption in a population.

Social Media Analytics Projects

Analyzing the engagement metrics of posts on a social media platform.
Researching the correlation between social media usage & mental health.
Exploring the effect of influencer marketing on consumer behavior.
Analyzing the demographics of users on a specific social media platform.
Investigating trends in hashtag usage on a popular social media site.

Education Statistics Projects

Analyzing the correlation between class size and student performance.
Investigating the impact of extracurricular activities on academic achievement.
Studying the distribution of standardized test scores in different schools.
Researching the effectiveness of online learning platforms in student outcomes.
Investigating the factors influencing student dropout rates in a college.

Psychology and Behavior Projects

Analyzing the correlation between sleep patterns and stress levels.
Investigating the impact of music on mood and concentration.
Studying the relationship between personality types and career choices.
Analyzing the correlation between social media usage and self-esteem.
Investigating the factors influencing decision-making in a specific demographic.

Healthcare and Medical Statistics Projects

Analyzing the distribution of blood pressure levels in a patient population.
Investigating the correlation between physical activity and heart health.
Studying the effectiveness of a new treatment in patient recovery.
Analyzing the prevalence of a specific health condition in different age groups.
Investigating the correlation between diet and the occurrence of chronic diseases.

Sociology and Demography Projects

Analyzing the distribution of household sizes in a community.
Investigating the correlation between socio-economic status and education levels.
Studying the impact of immigration on demographic changes in a region.
Analyzing the distribution of family structures in different cultural contexts.
Investigating trends in marriage and divorce rates over time.

Business and Management Projects:

Analyzing the correlation between employee satisfaction and productivity.
Investigating the impact of leadership styles on team performance.
Studying the distribution of work hours in a specific industry.
Analyzing the factors influencing customer loyalty in a business.
Investigating the correlation between employee training and job satisfaction.

Crime and Justice Statistics Projects

Analyzing the distribution of crime rates in different neighborhoods.
Investigating the correlation between policing strategies and crime reduction.
Studying the impact of sentencing policies on prison populations.
Analyzing the distribution of types of crimes in urban and rural areas.
Investigating the correlation between socio-economic factors and crime rates.

Political Science and Governance Projects

Analyzing voter turnout in different elections and identifying trends.
Investigating the correlation between political advertising and election outcomes.
Studying the impact of government policies on public opinion.
Analyzing the distribution of political ideologies in a population.
Investigating the correlation between social media usage & political engagement.

Linguistics and Language Projects

Analyzing the distribution of language proficiency levels in a population.
Investigating the correlation between bilingualism and cognitive abilities.
Studying language changes over time in a specific region.
Analyzing the impact of language education programs on language skills.
Investigating the correlation between language use and cultural identity.

Geography and Urban Planning Projects

Analyzing the distribution of population density in urban areas.
Investigating the correlation between urbanization and environmental degradation.
Exploring the impact of transportation infrastructure on urban development.
Analyzing the distribution of land use in a city or region.
Investigating the correlation between housing affordability and income levels.

Marketing and Consumer Behavior Projects

Analyzing the effectiveness of different marketing strategies on product sales.
Investigating the correlation between product packaging and consumer preferences.
Researching the impact of online reviews on consumer purchasing decisions.
Analyzing the distribution of brand loyalty in a target market.
Investigating the correlation between advertising content and brand perception.
Studying the factors influencing impulse buying behavior in consumers.

These Statistics Project Ideas cover a wide range of topics and can be adapted to different levels of statistical analysis, making them suitable for both school and college students.

Also Read:- How To Use Chatgpt To Write A Scientific Research Paper

How Do You Start A Statistics Project?

Starting a statistics project is easy and involves a few simple steps:

Select a Topic: Choose a topic that interests you. It could be about your school, hobbies, or something you’ve observed daily.
Define Your Question: Clearly state what you want to find out. For example, if you’re looking at grades, your question could be, “Do study hours affect grades?”
Collect Data: Gather information related to your question. It could be survey responses, measurements, or observations. Use sources like surveys, online data, or personal observations.
Organize Your Data: Arrange your data neatly. Use tables, charts, or graphs to make it easy to understand.
Analyze the Data: Look for patterns or trends in your data. Are there any connections between the variables you studied?
Draw Conclusions: Based on your research, what can you say regarding your question? Does the data support any specific ideas or findings?
Create a Report: Share your project by making a simple report. Include your question, the data, your analysis, and your conclusions. Use visuals like charts or graphs to make it more interesting.
Review and Edit: Before presenting, review your project. Ensure your ideas are clear and easy to understand.

Remember, the key is to have fun and learn something new through your statistics project!

What Are Some Examples Of Statistics Projects?

Here are some examples of statistics project ideas.

Grades and Study Hours

Question: Does the number of study hours impact students’ grades?
Data: Collect study hours and grades from classmates.
Analysis: Correlate study hours with grades to see if there’s a relationship.

Social Media Usage

Question: What is the most used social media platform among students?
Data: Conduct a survey or gather usage data.
Analysis: Compare the popularity of different social media platforms.

Health and Exercise

Question: Is there a correlation between exercise and stress levels ?
Data: Collect self-reported exercise habits and stress levels.
Analysis: Examine if those who exercise more report lower stress.

Favorite Music Genres

Question: What are the most popular music genres among friends?
Data: Survey friends about their favorite music genres.
Analysis: Create a chart to display the distribution of preferences.

Screen Time and Sleep

Question: Does increased screen time affect sleep duration?
Data: Collect data on daily screen time and sleep hours.
Analysis: Investigate if there’s a correlation between screen time and sleep duration.

Final Remarks

In the world of numbers, we’ve explored many interesting statistics project ideas that uncover stories behind everyday data. From checking out study habits to understanding social media trends, these projects let you dive into the world of numbers in a fun way.

To start your own project, just pick a topic you like, ask a clear question, collect data, and tell a story with it. Whether you’re a student or just someone curious about data, these statistics project ideas make statistics not only easy but also fun. So, let’s keep making learning exciting by turning numbers into stories in the world of statistics!

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60 best statistics project ideas for a+ graders.

January 19, 2021

A good statistics project requires a hypothesis that is clearly defined. For this, you need a topic that sparks your interest. If your statistics research project ideas are very vague and do not have a proper direction, it is impossible to write a good hypothesis.

Of course, that is also the most challenging part of your statistics paper, whether you are in high school, an undergrad program or a post-grad program. Here are a list of easy statistics project ideas that are also very effective.

Statistics Project Ideas About College

There are several topics related to the lives of college students that provide you with a good scope for statistic project idea hypothesis testing:

The amount of time spent by college students on social media
The most popular type of music among college students
The differences between male and female college students with respect to web browsing habits.
Percentage of college seniors who are likely to get married within four years of completing graduation.
The effect of taking the back seat in a class or the front seat in the class on success rates of students
Comparative study on the pricing of different clothing store prices in your town.
Does caffeine consumption affect the performance of students in college?
Does the experience of a freshman in college with their roommate affect their overall experience at the institution?
Is there any relationship between birth order and success in academics?
Does the race of actors affect the popularity of TV shows among college students?
What makes a student more likely to choose a subject: liking of the subject or the industry’s stability?

Statistics Project Ideas About Business

Subjects related to business provide the best scope for statistics survey project ideas. Here are a few examples:

The accessibility to banks in various parts of the world
Do female employees experience more sexual harassment in the workplace?
Are Dutch people more blunt and direct when it comes to business? Build your statistics project topic ideas around famous Dutch businessmen
Does social media presence or influence affect the performance of an employee?
Is alcohol consumption higher among employees who are at the lower end of the pay scale?
Impact of cost control on the ability of businesses to reach their objective and goals
Trends of debt management in well-known business entities.
Study of the occupational schedules provided to secretaries.
Analysis of all the factors that contribute to low productivity in employees.
Analysis of the effect of assessment on the performance of workers in an organization.
The relationship between production system design and management in the soft drink industry.
Is cost-volume-profit analysis a useful tool to improve decision making within an organization
Effect of modern communication equipment on the performance of employees in an organization.

Socio-Economical Statistics Project Ideas

You can get great ideas for statistics projects by observing the world around you:

Statistical analysis of income versus expenditure in more impoverished neighbourhoods
Analysis of food habits in low-income groups.
Effect of agricultural loans on farming activities in the country.
Effect of poverty on crime rates.
Statistical analysis of the relationship between malpractices in examinations and income groups of students
Statistical analysis of the criminal offences recorded in your town or country.
Statistical analysis of road accidents in a given suburb or area in your town.
Statistical analysis of peak traffic times in your city
Statistical analysis of psychosocial dysfunction and effect on performance at the workplace
Statistical analysis of the impact of smoking on medical costs
Is there a relationship between exercise and reduction in overall medical costs?
A complete analysis of the impact of per capita income on health care expenses
Statistical analysis of the impact of birth and death rates on the economy of a country
Analysis of the impact of petroleum prices on food prices
Statistical analysis of the effect of training and development activities within an organization on an employee’s performance.
Analysis of the sources of revenue and the pattern of expenditure of the local government.
Are computerized budget analysis systems effective?
The primary contributors to financial distress in the banking sector
Analysis of the use of financial reports in assessing the performance of banks.
Analysis of cash deposit patterns in banks.
Are members of certain subpopulations more likely to get a death penalty?
Do debt reduction policies of the government also reduce the quality of life?
Is there any relationship between AIDS prevalence and female empowerment?
Do federal elections affect the stock prices?

Basic statistical tools in research and data analysis

Zulfiqar ali.

Department of Anaesthesiology, Division of Neuroanaesthesiology, Sheri Kashmir Institute of Medical Sciences, Soura, Srinagar, Jammu and Kashmir, India

S Bala Bhaskar

1 Department of Anaesthesiology and Critical Care, Vijayanagar Institute of Medical Sciences, Bellary, Karnataka, India

Statistical methods involved in carrying out a study include planning, designing, collecting data, analysing, drawing meaningful interpretation and reporting of the research findings. The statistical analysis gives meaning to the meaningless numbers, thereby breathing life into a lifeless data. The results and inferences are precise only if proper statistical tests are used. This article will try to acquaint the reader with the basic research tools that are utilised while conducting various studies. The article covers a brief outline of the variables, an understanding of quantitative and qualitative variables and the measures of central tendency. An idea of the sample size estimation, power analysis and the statistical errors is given. Finally, there is a summary of parametric and non-parametric tests used for data analysis.

INTRODUCTION

Statistics is a branch of science that deals with the collection, organisation, analysis of data and drawing of inferences from the samples to the whole population.[ 1 ] This requires a proper design of the study, an appropriate selection of the study sample and choice of a suitable statistical test. An adequate knowledge of statistics is necessary for proper designing of an epidemiological study or a clinical trial. Improper statistical methods may result in erroneous conclusions which may lead to unethical practice.[ 2 ]

Variable is a characteristic that varies from one individual member of population to another individual.[ 3 ] Variables such as height and weight are measured by some type of scale, convey quantitative information and are called as quantitative variables. Sex and eye colour give qualitative information and are called as qualitative variables[ 3 ] [ Figure 1 ].

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Classification of variables

Quantitative variables

Quantitative or numerical data are subdivided into discrete and continuous measurements. Discrete numerical data are recorded as a whole number such as 0, 1, 2, 3,… (integer), whereas continuous data can assume any value. Observations that can be counted constitute the discrete data and observations that can be measured constitute the continuous data. Examples of discrete data are number of episodes of respiratory arrests or the number of re-intubations in an intensive care unit. Similarly, examples of continuous data are the serial serum glucose levels, partial pressure of oxygen in arterial blood and the oesophageal temperature.

A hierarchical scale of increasing precision can be used for observing and recording the data which is based on categorical, ordinal, interval and ratio scales [ Figure 1 ].

Categorical or nominal variables are unordered. The data are merely classified into categories and cannot be arranged in any particular order. If only two categories exist (as in gender male and female), it is called as a dichotomous (or binary) data. The various causes of re-intubation in an intensive care unit due to upper airway obstruction, impaired clearance of secretions, hypoxemia, hypercapnia, pulmonary oedema and neurological impairment are examples of categorical variables.

Ordinal variables have a clear ordering between the variables. However, the ordered data may not have equal intervals. Examples are the American Society of Anesthesiologists status or Richmond agitation-sedation scale.

Interval variables are similar to an ordinal variable, except that the intervals between the values of the interval variable are equally spaced. A good example of an interval scale is the Fahrenheit degree scale used to measure temperature. With the Fahrenheit scale, the difference between 70° and 75° is equal to the difference between 80° and 85°: The units of measurement are equal throughout the full range of the scale.

Ratio scales are similar to interval scales, in that equal differences between scale values have equal quantitative meaning. However, ratio scales also have a true zero point, which gives them an additional property. For example, the system of centimetres is an example of a ratio scale. There is a true zero point and the value of 0 cm means a complete absence of length. The thyromental distance of 6 cm in an adult may be twice that of a child in whom it may be 3 cm.

STATISTICS: DESCRIPTIVE AND INFERENTIAL STATISTICS

Descriptive statistics[ 4 ] try to describe the relationship between variables in a sample or population. Descriptive statistics provide a summary of data in the form of mean, median and mode. Inferential statistics[ 4 ] use a random sample of data taken from a population to describe and make inferences about the whole population. It is valuable when it is not possible to examine each member of an entire population. The examples if descriptive and inferential statistics are illustrated in Table 1 .

Example of descriptive and inferential statistics

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Descriptive statistics

The extent to which the observations cluster around a central location is described by the central tendency and the spread towards the extremes is described by the degree of dispersion.

Measures of central tendency

The measures of central tendency are mean, median and mode.[ 6 ] Mean (or the arithmetic average) is the sum of all the scores divided by the number of scores. Mean may be influenced profoundly by the extreme variables. For example, the average stay of organophosphorus poisoning patients in ICU may be influenced by a single patient who stays in ICU for around 5 months because of septicaemia. The extreme values are called outliers. The formula for the mean is

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where x = each observation and n = number of observations. Median[ 6 ] is defined as the middle of a distribution in a ranked data (with half of the variables in the sample above and half below the median value) while mode is the most frequently occurring variable in a distribution. Range defines the spread, or variability, of a sample.[ 7 ] It is described by the minimum and maximum values of the variables. If we rank the data and after ranking, group the observations into percentiles, we can get better information of the pattern of spread of the variables. In percentiles, we rank the observations into 100 equal parts. We can then describe 25%, 50%, 75% or any other percentile amount. The median is the 50 th percentile. The interquartile range will be the observations in the middle 50% of the observations about the median (25 th -75 th percentile). Variance[ 7 ] is a measure of how spread out is the distribution. It gives an indication of how close an individual observation clusters about the mean value. The variance of a population is defined by the following formula:

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where σ 2 is the population variance, X is the population mean, X i is the i th element from the population and N is the number of elements in the population. The variance of a sample is defined by slightly different formula:

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where s 2 is the sample variance, x is the sample mean, x i is the i th element from the sample and n is the number of elements in the sample. The formula for the variance of a population has the value ‘ n ’ as the denominator. The expression ‘ n −1’ is known as the degrees of freedom and is one less than the number of parameters. Each observation is free to vary, except the last one which must be a defined value. The variance is measured in squared units. To make the interpretation of the data simple and to retain the basic unit of observation, the square root of variance is used. The square root of the variance is the standard deviation (SD).[ 8 ] The SD of a population is defined by the following formula:

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where σ is the population SD, X is the population mean, X i is the i th element from the population and N is the number of elements in the population. The SD of a sample is defined by slightly different formula:

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where s is the sample SD, x is the sample mean, x i is the i th element from the sample and n is the number of elements in the sample. An example for calculation of variation and SD is illustrated in Table 2 .

Example of mean, variance, standard deviation

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Normal distribution or Gaussian distribution

Most of the biological variables usually cluster around a central value, with symmetrical positive and negative deviations about this point.[ 1 ] The standard normal distribution curve is a symmetrical bell-shaped. In a normal distribution curve, about 68% of the scores are within 1 SD of the mean. Around 95% of the scores are within 2 SDs of the mean and 99% within 3 SDs of the mean [ Figure 2 ].

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Normal distribution curve

Skewed distribution

It is a distribution with an asymmetry of the variables about its mean. In a negatively skewed distribution [ Figure 3 ], the mass of the distribution is concentrated on the right of Figure 1 . In a positively skewed distribution [ Figure 3 ], the mass of the distribution is concentrated on the left of the figure leading to a longer right tail.

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Curves showing negatively skewed and positively skewed distribution

Inferential statistics

In inferential statistics, data are analysed from a sample to make inferences in the larger collection of the population. The purpose is to answer or test the hypotheses. A hypothesis (plural hypotheses) is a proposed explanation for a phenomenon. Hypothesis tests are thus procedures for making rational decisions about the reality of observed effects.

Probability is the measure of the likelihood that an event will occur. Probability is quantified as a number between 0 and 1 (where 0 indicates impossibility and 1 indicates certainty).

In inferential statistics, the term ‘null hypothesis’ ( H 0 ‘ H-naught ,’ ‘ H-null ’) denotes that there is no relationship (difference) between the population variables in question.[ 9 ]

Alternative hypothesis ( H 1 and H a ) denotes that a statement between the variables is expected to be true.[ 9 ]

The P value (or the calculated probability) is the probability of the event occurring by chance if the null hypothesis is true. The P value is a numerical between 0 and 1 and is interpreted by researchers in deciding whether to reject or retain the null hypothesis [ Table 3 ].

P values with interpretation

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If P value is less than the arbitrarily chosen value (known as α or the significance level), the null hypothesis (H0) is rejected [ Table 4 ]. However, if null hypotheses (H0) is incorrectly rejected, this is known as a Type I error.[ 11 ] Further details regarding alpha error, beta error and sample size calculation and factors influencing them are dealt with in another section of this issue by Das S et al .[ 12 ]

Illustration for null hypothesis

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PARAMETRIC AND NON-PARAMETRIC TESTS

Numerical data (quantitative variables) that are normally distributed are analysed with parametric tests.[ 13 ]

Two most basic prerequisites for parametric statistical analysis are:

The assumption of normality which specifies that the means of the sample group are normally distributed
The assumption of equal variance which specifies that the variances of the samples and of their corresponding population are equal.

However, if the distribution of the sample is skewed towards one side or the distribution is unknown due to the small sample size, non-parametric[ 14 ] statistical techniques are used. Non-parametric tests are used to analyse ordinal and categorical data.

Parametric tests

The parametric tests assume that the data are on a quantitative (numerical) scale, with a normal distribution of the underlying population. The samples have the same variance (homogeneity of variances). The samples are randomly drawn from the population, and the observations within a group are independent of each other. The commonly used parametric tests are the Student's t -test, analysis of variance (ANOVA) and repeated measures ANOVA.

Student's t -test

Student's t -test is used to test the null hypothesis that there is no difference between the means of the two groups. It is used in three circumstances:

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where X = sample mean, u = population mean and SE = standard error of mean

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where X 1 − X 2 is the difference between the means of the two groups and SE denotes the standard error of the difference.

To test if the population means estimated by two dependent samples differ significantly (the paired t -test). A usual setting for paired t -test is when measurements are made on the same subjects before and after a treatment.

The formula for paired t -test is:

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where d is the mean difference and SE denotes the standard error of this difference.

The group variances can be compared using the F -test. The F -test is the ratio of variances (var l/var 2). If F differs significantly from 1.0, then it is concluded that the group variances differ significantly.

Analysis of variance

The Student's t -test cannot be used for comparison of three or more groups. The purpose of ANOVA is to test if there is any significant difference between the means of two or more groups.

In ANOVA, we study two variances – (a) between-group variability and (b) within-group variability. The within-group variability (error variance) is the variation that cannot be accounted for in the study design. It is based on random differences present in our samples.

However, the between-group (or effect variance) is the result of our treatment. These two estimates of variances are compared using the F-test.

A simplified formula for the F statistic is:

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where MS b is the mean squares between the groups and MS w is the mean squares within groups.

Repeated measures analysis of variance

As with ANOVA, repeated measures ANOVA analyses the equality of means of three or more groups. However, a repeated measure ANOVA is used when all variables of a sample are measured under different conditions or at different points in time.

As the variables are measured from a sample at different points of time, the measurement of the dependent variable is repeated. Using a standard ANOVA in this case is not appropriate because it fails to model the correlation between the repeated measures: The data violate the ANOVA assumption of independence. Hence, in the measurement of repeated dependent variables, repeated measures ANOVA should be used.

Non-parametric tests

When the assumptions of normality are not met, and the sample means are not normally, distributed parametric tests can lead to erroneous results. Non-parametric tests (distribution-free test) are used in such situation as they do not require the normality assumption.[ 15 ] Non-parametric tests may fail to detect a significant difference when compared with a parametric test. That is, they usually have less power.

As is done for the parametric tests, the test statistic is compared with known values for the sampling distribution of that statistic and the null hypothesis is accepted or rejected. The types of non-parametric analysis techniques and the corresponding parametric analysis techniques are delineated in Table 5 .

Analogue of parametric and non-parametric tests

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Median test for one sample: The sign test and Wilcoxon's signed rank test

The sign test and Wilcoxon's signed rank test are used for median tests of one sample. These tests examine whether one instance of sample data is greater or smaller than the median reference value.

This test examines the hypothesis about the median θ0 of a population. It tests the null hypothesis H0 = θ0. When the observed value (Xi) is greater than the reference value (θ0), it is marked as+. If the observed value is smaller than the reference value, it is marked as − sign. If the observed value is equal to the reference value (θ0), it is eliminated from the sample.

If the null hypothesis is true, there will be an equal number of + signs and − signs.

The sign test ignores the actual values of the data and only uses + or − signs. Therefore, it is useful when it is difficult to measure the values.

Wilcoxon's signed rank test

There is a major limitation of sign test as we lose the quantitative information of the given data and merely use the + or – signs. Wilcoxon's signed rank test not only examines the observed values in comparison with θ0 but also takes into consideration the relative sizes, adding more statistical power to the test. As in the sign test, if there is an observed value that is equal to the reference value θ0, this observed value is eliminated from the sample.

Wilcoxon's rank sum test ranks all data points in order, calculates the rank sum of each sample and compares the difference in the rank sums.

Mann-Whitney test

It is used to test the null hypothesis that two samples have the same median or, alternatively, whether observations in one sample tend to be larger than observations in the other.

Mann–Whitney test compares all data (xi) belonging to the X group and all data (yi) belonging to the Y group and calculates the probability of xi being greater than yi: P (xi > yi). The null hypothesis states that P (xi > yi) = P (xi < yi) =1/2 while the alternative hypothesis states that P (xi > yi) ≠1/2.

Kolmogorov-Smirnov test

The two-sample Kolmogorov-Smirnov (KS) test was designed as a generic method to test whether two random samples are drawn from the same distribution. The null hypothesis of the KS test is that both distributions are identical. The statistic of the KS test is a distance between the two empirical distributions, computed as the maximum absolute difference between their cumulative curves.

Kruskal-Wallis test

The Kruskal–Wallis test is a non-parametric test to analyse the variance.[ 14 ] It analyses if there is any difference in the median values of three or more independent samples. The data values are ranked in an increasing order, and the rank sums calculated followed by calculation of the test statistic.

Jonckheere test

In contrast to Kruskal–Wallis test, in Jonckheere test, there is an a priori ordering that gives it a more statistical power than the Kruskal–Wallis test.[ 14 ]

Friedman test

The Friedman test is a non-parametric test for testing the difference between several related samples. The Friedman test is an alternative for repeated measures ANOVAs which is used when the same parameter has been measured under different conditions on the same subjects.[ 13 ]

Tests to analyse the categorical data

Chi-square test, Fischer's exact test and McNemar's test are used to analyse the categorical or nominal variables. The Chi-square test compares the frequencies and tests whether the observed data differ significantly from that of the expected data if there were no differences between groups (i.e., the null hypothesis). It is calculated by the sum of the squared difference between observed ( O ) and the expected ( E ) data (or the deviation, d ) divided by the expected data by the following formula:

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A Yates correction factor is used when the sample size is small. Fischer's exact test is used to determine if there are non-random associations between two categorical variables. It does not assume random sampling, and instead of referring a calculated statistic to a sampling distribution, it calculates an exact probability. McNemar's test is used for paired nominal data. It is applied to 2 × 2 table with paired-dependent samples. It is used to determine whether the row and column frequencies are equal (that is, whether there is ‘marginal homogeneity’). The null hypothesis is that the paired proportions are equal. The Mantel-Haenszel Chi-square test is a multivariate test as it analyses multiple grouping variables. It stratifies according to the nominated confounding variables and identifies any that affects the primary outcome variable. If the outcome variable is dichotomous, then logistic regression is used.

SOFTWARES AVAILABLE FOR STATISTICS, SAMPLE SIZE CALCULATION AND POWER ANALYSIS

Numerous statistical software systems are available currently. The commonly used software systems are Statistical Package for the Social Sciences (SPSS – manufactured by IBM corporation), Statistical Analysis System ((SAS – developed by SAS Institute North Carolina, United States of America), R (designed by Ross Ihaka and Robert Gentleman from R core team), Minitab (developed by Minitab Inc), Stata (developed by StataCorp) and the MS Excel (developed by Microsoft).

There are a number of web resources which are related to statistical power analyses. A few are:

StatPages.net – provides links to a number of online power calculators
G-Power – provides a downloadable power analysis program that runs under DOS
Power analysis for ANOVA designs an interactive site that calculates power or sample size needed to attain a given power for one effect in a factorial ANOVA design
SPSS makes a program called SamplePower. It gives an output of a complete report on the computer screen which can be cut and paste into another document.

It is important that a researcher knows the concepts of the basic statistical methods used for conduct of a research study. This will help to conduct an appropriately well-designed study leading to valid and reliable results. Inappropriate use of statistical techniques may lead to faulty conclusions, inducing errors and undermining the significance of the article. Bad statistics may lead to bad research, and bad research may lead to unethical practice. Hence, an adequate knowledge of statistics and the appropriate use of statistical tests are important. An appropriate knowledge about the basic statistical methods will go a long way in improving the research designs and producing quality medical research which can be utilised for formulating the evidence-based guidelines.

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PSY4401 - Psychology research project: Statistics and research design for professional psychology - 2019

6 points, sca band 1, 0.125 eftsl, postgraduate - unit.

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.

Medicine, Nursing and Health Sciences

Organisational Unit

School of Psychological Sciences

Chief examiner(s)

Dr Stephen McKenzie

Coordinator(s)

Dr Janelle Levesque

Unit guides

Teaching Period 1

Monash Online

Teaching Period 1 2019 (Online)
Teaching Period 3 2019 (Online)
Teaching Period 5 2019 (Online)

Prerequisites

Completed Bachelor's Degree and a major sequence in psychology approved by the Australian Psychological Society, or qualification assessed as equivalent by the Australian Psychological Society, with a distinction average (70%) for third year psychology units.

Co-requisites

Must be enrolled in Graduate Diploma of Psychology Advanced (M5003)

Prohibitions

PSY4001, PSY4002, PSY4011, PSY4012, PSY4021, PSY4022, PSY4100 and PSY4210

Students are required to finalise the Monash University Human Research Ethics Committee (MUHREC) application and receive approval from MUHREC prior to commencement of enrolment in PSY4403.

The aim of this unit is to provide students with a thorough understanding of statistical concepts to enable them to be informed in their chosen field. The unit begins with a review of univariate statistics and introduction to the philosophy of research design and analysis. More advanced statistical techniques are then systematically introduced. There is a focus on the understanding of the issues that may arise around the choice of appropriate statistical technique and preparation of data; critiquing decisions made to assist in the interpretation of findings. The content will be set in a context of the needs of professional psychologists and researchers whose interests present unusual methodological demands, which in turn may influence choices in research approach and statistical technique.

Upon successful completion of this unit, students should be able to:

Describe a range of methodological and philosophical principles in research design, analysis and interpretation;
Describe, apply and evaluate research designs and analyses used by psychologists;
Apply scientific research principles to data in practice;
Critique data with a view to preparation, analysis and interpretation;
Operate SPSS to analyse data for analysis;
Critique and record decisions made in the process of research examples distinguishing between fact and inference in sets of analyses.
Essay (1,500 words) (30%)
Lab report (2,000 words) (40%) (hurdle)
6 x Secure multiple choice quizzes (20 minutes each) (30% total)

Workload requirements

Students should expect to spend an average of 20-25 hours per week per unit. Broadly, this time will cover:

Video materials (2hrs)

Synchronous & asynchronous discussion (2hrs)

Synchronous web-based 'class-time' for skills-based activities (2hrs)

Weekly readings (4-6hrs)

Weekly skills-based assessment (4-6hrs, including formative assessment)

Knowledge-based assessment (4-5hrs, including revision)

This unit applies to the following area(s) of study

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Knowledge Base

Methodology

Research Methods | Definitions, Types, Examples

Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design . When planning your methods, there are two key decisions you will make.

First, decide how you will collect data . Your methods depend on what type of data you need to answer your research question :

Qualitative vs. quantitative : Will your data take the form of words or numbers?
Primary vs. secondary : Will you collect original data yourself, or will you use data that has already been collected by someone else?
Descriptive vs. experimental : Will you take measurements of something as it is, or will you perform an experiment?

Second, decide how you will analyze the data .

For quantitative data, you can use statistical analysis methods to test relationships between variables.
For qualitative data, you can use methods such as thematic analysis to interpret patterns and meanings in the data.

Methods for collecting data, examples of data collection methods, methods for analyzing data, examples of data analysis methods, other interesting articles, frequently asked questions about research methods.

Data is the information that you collect for the purposes of answering your research question . The type of data you need depends on the aims of your research.

Qualitative vs. quantitative data

Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.

For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data .

If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing , collect quantitative data .

You can also take a mixed methods approach , where you use both qualitative and quantitative research methods.

Primary vs. secondary research

Primary research is any original data that you collect yourself for the purposes of answering your research question (e.g. through surveys , observations and experiments ). Secondary research is data that has already been collected by other researchers (e.g. in a government census or previous scientific studies).

If you are exploring a novel research question, you’ll probably need to collect primary data . But if you want to synthesize existing knowledge, analyze historical trends, or identify patterns on a large scale, secondary data might be a better choice.

Descriptive vs. experimental data

In descriptive research , you collect data about your study subject without intervening. The validity of your research will depend on your sampling method .

In experimental research , you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design .

To conduct an experiment, you need to be able to vary your independent variable , precisely measure your dependent variable, and control for confounding variables . If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.

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Your data analysis methods will depend on the type of data you collect and how you prepare it for analysis.

Data can often be analyzed both quantitatively and qualitatively. For example, survey responses could be analyzed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.

Qualitative analysis methods

Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that was collected:

From open-ended surveys and interviews , literature reviews , case studies , ethnographies , and other sources that use text rather than numbers.
Using non-probability sampling methods .

Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions and be careful to avoid research bias .

Quantitative analysis methods

Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).

You can use quantitative analysis to interpret data that was collected either:

During an experiment .
Using probability sampling methods .

Because the data is collected and analyzed in a statistically valid way, the results of quantitative analysis can be easily standardized and shared among researchers.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

Chi square test of independence
Statistical power
Descriptive statistics
Degrees of freedom
Pearson correlation
Null hypothesis
Double-blind study
Case-control study
Research ethics
Data collection
Hypothesis testing
Structured interviews

Research bias

Hawthorne effect
Unconscious bias
Recall bias
Halo effect
Self-serving bias
Information bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

The research methods you use depend on the type of data you need to answer your research question .

If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

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Enhancing Food Security and Income for Smallholder Farmers in Angola

Photo credit: Wilson Piassa, World Bank

“ The irrigation canal that our community has through the project allows us to continue to work the land and harvest crops satisfactorily all year round even when it doesn't rain . Another gain for me, and many other women, is that now, before we plant, we know how to calculate the cost and benefit of what we grow. We also know which products are appropriate for each plot of land. The farmer field schools have been of great value to us.”

Maria Mateus, Chissapa Farmers’ Association, Camacupa municipality, Bie province.

Angola’s agricultural sector was devastated by the Angolan civil war of 1975–2002, resulting in very low agricultural production and heavy reliance on food imports, sustained by oil revenue. But when oil prices dropped by over 72 percent between March 2014 and March 2016, a fiscal crisis ensued that threatened food security and prompted the government of Angola to accelerate domestic agricultural production. This required addressing key constraints, including its weak capacity for planning and advisory services, limited use of improved agricultural practices and technologies, limited access to modern inputs (including seeds and fertilizers), inadequate market information, and high post-harvest losses.

The Angola Smallholder Agriculture Development and Commercialization Project ’s development objective was to increase smallholder agriculture productivity, production, and marketing for selected crops in the project areas (the central and northern provinces of Bie, Huambo, and Malanje). These provinces, once at the epicenter of the civil war, had great agricultural potential. World Bank involvement brought global experience and knowledge on pro-poor agriculture programs for smallholders. The project launched in 2016 and set up 4,000 Farmer Field Schools (FFSs) to strengthen smallholder farmers’ technical, organizational, and managerial capacities. The Ministry of Agriculture and Forestry (MINAGRIF) relied on technical assistance from the Food and Agriculture Organization of the United Nations (FAO) to implement capacity-building activities that benefited over 150,000 smallholder farmers. These skills development programs were complemented by facilitating farmers’ access to agricultural inputs and markets through a value chain development approach.

Between 2016 and 2022, the project implemented 4,000 FFS, benefiting 179,000 people (of whom 49 percent were women), helping them to increase agricultural productivity, agricultural production, and the proportion of produce sold. The main crops supported by the project were maize, cassava, beans, potatoes, tomatoes, and cabbage. The FFSs were very effective at increasing the ability of small farmers to adopt the new agricultural practices promoted by the project and increasing productivity. In turn, this allowed project beneficiaries to improve their incomes and promoted food security.

The average crop yield of targeted crops increased by 65 percent to 196 percent compared to the baseline. Compared to project non-beneficiaries, project beneficiaries had higher yields. The yield differentials ranging from 5 percent to 86 percent. The highest yield differential was maize with 86 percent, 67 percent for beans, 63 percent for potatoes, 28% for cassava, and 5% for tomatoes.
Aggregate crop production increased by 64 percent over the baseline and exceeded project targets by 16 percent.
The proportion of production sold by smallholder farmers was estimated to have increased from a baseline of 17 percent to 69 percent at project closing.
Due to substantial increases in productivity, production, and the proportion of production sold, project beneficiaries had created, in total, 240 savings and credit groups by October 2021, with estimated savings amounting to the equivalent of $500, 000.
As a result of the project’s interventions, the Angolan Government reported increased social expenditure among project beneficiaries (including spending on better housing, children’s education, and transport), as well as the purchase and use of modern agricultural inputs.

Bank Group Contribution

The total project cost was $95 million, of which $20 million equivalent was an in-kind and cash contribution by the government of Angola and $5 million equivalent was in-kind by project beneficiaries mainly coming under matching grants and their improved income from increased sales. A $70 million IBRD loan constituted the remainder of the total project cost.

FAO was the main partner and provided technical assistance to establish 4,000 FFSs out of the 5,000 planned for the project. The project collaborated with renowned international centers of excellence, namely the International Institute of Tropical Agriculture, International Potato Center, and International Maize and Wheat Improvement Center to acquire improved planting material for local testing (for adaptability), thus expediting innovation.

Looking Ahead

FFS Manuals have been prepared and training provided to Angola’s Agrarian Development Institute at MINAGRIF to help entrench the project’s approach in the country’s agricultural extension delivery systems. The Smallholder Agricultural Transformation Project (MOSAP 3), for $300 million in IBRD financing, was approved by the World Bank in June 2022, and will support Angola in building on the successes of MOSAP2.

Smallholder Agriculture Development and Commercialization Project

Farmers’ Field Schools Pave the way to Better Agricultural Prospects in Angola

The World Bank in Angola

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In states with laws targeting LGBTQ issues, school hate crimes quadrupled

School hate crimes targeting LGBTQ+ people have sharply risen in recent years, climbing fastest in states that have passed laws restricting LGBTQ+ student rights and education, a Washington Post analysis of FBI data finds.

In states with restrictive laws, the number of hate crimes on K-12 campuses has more than quadrupled since the onset of a divisive culture war that has often centered on the rights of LGBTQ+ youth.

At the same time, calls to LGBTQ+ youth crisis hotlines have exploded, with some advocates drawing a connection between the political climate and the spike in bullying and hate crimes.

Tell The Post: Do you have experience with anti-LGBTQ+ bullying at school?

LGBTQ+ students have long dealt with bullying and harassment at school, but some students are feeling particularly vulnerable due to the wave of legislation. They are also on edge following the death of Nex Benedict, a nonbinary teenager who died after a fight in their Oklahoma public school bathroom. The death was ruled a suicide, according to a one-page summary report released Wednesday by the state’s chief medical examiner.

That’s the case for Carden, a transgender 17-year-old. He argues that politicians’ anti-LGBTQ+ rhetoric has shaped the views of adults in the conservative Virginia county where he lives.

“Kids parrot these ideas in their head, it’s like, ‘Oh, my parents think …’” said Carden, whose parents asked that his last name be withheld for fear of further bullying. “Then it translates to being mean to other people their age.”

Twice in the fall, a group of freshmen boys at Carden’s school harassed him for his gender identity — once calling him “queer” in a nasty tone, he said. The second time, after telling him a Pride flag he had tucked into his backpack was “pitiful,” one of the boys suggested Carden should “just go die already.”

Since his election in 2021, Virginia Gov. Glenn Youngkin (R) has encouraged schools to require that students use facilities matching their biological sex and has signed a law requiring schools to alert parents of “sexually explicit” lessons, alarming LGBTQ+ advocacy groups, which predicted it would be used to limit education on sexual orientation and gender identity. Other Republican governors have advanced similar policies through executive action and legislation.

Podcast episode

The Post analysis found that the number of anti-LGBTQ+ school hate crimes serious enough to be reported to local police more than doubled nationwide between 2015-2019 and 2021-2022. The rise is steeper in the 28 states that have passed laws curbing the rights of transgender students at school and restricting how teachers can talk about issues of gender and sexuality.

In more-liberal states that have not enacted restrictive school LGBTQ+ laws, The Post found that the rise in FBI hate crimes was lower — though the absolute number of crimes was higher. Analysts said that may be because people in those states are more likely to report incidents.

Advocacy groups have also seen a rising number of young people in distress.

Calls have spiked to the Trevor Project, which provides support to LGBTQ+ youth aimed at suicide prevention and crisis intervention. In the fiscal year ending in July 2022, the group fielded about 230,000 crisis contacts, including phone calls, texts and online chats. The following year, it was more than 500,000.

Similarly, the Rainbow Youth Project , a nonprofit that offers crisis response and counseling to at-risk LGBTQ+ youth, saw calls to its hotline rise from an average of about 1,000 per month in 2022 to just over 1,400 per month last year. The top reason cited by callers in 2023 was anti-LGBTQ+ “political rhetoric,” such as debate over laws and policies limiting rights at school.

Young people will say, “‘My government hates me,’ ‘My school hates me,’ ‘They don’t want me to exist,’” said Lance Preston, the group’s founder and executive director. “That ... is absolutely unacceptable. That is shocking.”

How The Post reported on anti-LGBTQ hate at school

In the weeks after Nex’s death, the Rainbow Youth Project saw a crush of calls from Oklahoma, rising from 321 in January to nearly 1,100 in February, though the surge may have been driven at least in part by news coverage of the group’s work.

Nex, who used they/them pronouns, died on Feb. 8, a day after a confrontation in the bathroom of their school in a Tulsa suburb. School officials sent the students home, but Nex’s grandmother took Nex to the hospital later that day and called police.

In a statement to an officer, Nex and their grandmother said three girls had been bullying Nex and a friend because of how they dress. In the bathroom that day, these girls were making comments Nex found offensive, and Nex poured water on them. Then “all three of them came at me,” Nex said. A fight ensued.

Nex was discharged from the hospital but rushed back the next day, when they died. The case has drawn national attention. Before the cause of death was released, LGBTQ+ advocates argued that Nex was bullied and that their death was a hate crime related to their gender identity. After the finding of suicide was made public, they connected the suicide to the bullying. The Office for Civil Rights at the Department of Education this month opened an investigation into the school’s actions.

Since 2020, Oklahoma has adopted several laws restricting transgender rights. The state prohibits students from using bathrooms that do not align with the sex assigned at their birth and bars minors from receiving transition-related care. The legislature is considering additional measures this year, including a ban on changing one’s gender on birth certificates and requiring that schools teach that “a person’s sex is an immutable biological trait” that cannot be changed.

Many of these bills have been championed by the state’s schools superintendent, Ryan Walters, who said in an interview that Nex’s death was a heartbreaking tragedy, but that those who are connecting it to bullying or gender identity are pushing a “left-wing agenda” and “politicizing the death of a student.”

Va. killed bills aimed at trans youths. Here’s where the debate moves next.

Walters said he will continue to push for legislation to counter what he called “radical gender theory,” which he defines as the notion that one’s gender can differ from biological sex.

“There’s two genders. That’s the way God created us,” Walters said. Some young people are confused, he said, but, “your job as an adult is to help kids, not lie to them.”

He added that he opposes bullying but wholly rejects the idea that the political environment is encouraging it.

“Because you share a belief or an opinion does not mean it’s connected to violence,” he said.

Hate crimes on the rise

The FBI data shows serious incidents against LGBTQ+ people are on the rise, particularly in the more than two dozen states that have passed laws targeting LGBTQ+ students or education. Some of these laws, like those enacted in Oklahoma, bar students from competing on sports teams or using school bathrooms that do not conform with their sex assigned at birth. Others circumscribe what teachers can teach about gender identity or sexual orientation or bar instruction on these subjects entirely.

Overall, there were an average of 108 anti-LGBTQ+ hate crimes at schools reported to the FBI per year from 2015 to 2019 on both college and K-12 campuses. In 2021 and 2022, the most recent years for which data was available, the average more than doubled to 232. (The number of reported hate crimes overall dropped in 2020, when the covid-19 pandemic shut down many school campuses, forcing learning online.)

The rise was even steeper in states that have enacted laws or policies which restrict LGBTQ+ students’ education or rights at school — tripling from an average of about 28 per year from 2015 to 2019 to an average of about 90 per year in 2021 to 2022. There was also an upsurge in the states without these laws, from about 79 reported hate crimes per year to 140.

When the data is limited to K-12 campuses, the increase is even more marked. In states that have enacted restrictive laws, there were more than four times the number of anti-LGBTQ+ hate crimes on average, per year, in 2021 to 2022 compared with the years 2015 to 2019 across elementary, middle and high schools.

“Policy sets the tone for real-world experiences [and] discriminatory policy just creates a hostile environment,” said Amy McGehee, a doctoral student at Oklahoma State University who researches LGBTQ+ health and well-being.

FBI data indicate the most common crimes associated with reported hate crimes at schools include simple assault, intimidation and vandalism.

McGehee added that LGBTQ+ students were reporting feeling unsafe on both college and K-12 campuses even before states began passing waves of policies restricting their rights at school. A sweeping Washington Post-KFF poll last year found that school is among the greatest stressors for transgender children in particular. Forty-five percent of trans adults said they felt generally unsafe at school as a child or teenager, compared with 10 percent of cisgender adults.

Trans kids crave acceptance at school in a nation that often resists it

The Post’s analysis of FBI data found that the per capita hate crime rates on K-12 and college campuses were higher in the more liberal states that have not enacted laws limiting transgender rights. Although the finding may seem counterintuitive, it actually makes sense, said Stephen Russell, a University of Texas at Austin professor who studies LGBTQ+ youth. He said LGBTQ+ youth and families living in those 22 states were probably more likely to report violence and harassment in the first place.

Many of these states have adopted laws and school policies specifically prohibiting bullying of or discrimination against LGBTQ+ students, he said. In some places, he said, that includes required annual notifications alerting students and parents to their rights and spelling out how they can and should report bad behavior.

“It creates a context where they see themselves, they stand up for themselves, they believe there is a place for them in their schools,” Russell said of LGBTQ+ children.

In addition, it’s possible more kids are public about their identities in more liberal states, creating more targets for bullies, said Lanae Erickson, a senior vice president at Third Way, a centrist Democratic think tank, who studies social policy and politics.

Both Erickson and Russell were unsurprised to learn that the number of hate crimes had risen faster in states with conservative laws.

“The data you have is the thing I’ve been worrying about, and here it is,” said Russell.

‘They don’t want us to exist’

The upsurge in restrictive laws and in school bullying has left some LGBTQ+ students feeling under attack.

Last year, classmates regularly harassed a transgender teenager in Mississippi for his short hair and for wearing boy’s clothing and chest binders, his mother said in an interview. Throughout that year, her son often woke up in the middle of the night vomiting due to stress. He wound up missing about three weeks of school due to bullying-induced breakdowns, recalled the mother, who spoke on the condition of anonymity for fear of retaliation from family members who do not support her son’s gender identity.

She said her son has been suicidal at times, at one point keeping a journal in which he detailed plans to kill himself. She said he also cut himself. “He feels shamed,” she said. “It’s hard for him to find friends.”

In 2021, Mississippi enacted a law barring transgender students from playing on sports teams that match their gender identity. Partly citing that state policy, the mother said she feels like everything is just getting worse.

“I’m really worried that my child is getting irreparable mental damage from all of this,” she said. “I also just get worried that, what if he gets suicidal again? I don’t want to lose my son.”

Studies show that LGBTQ+ youth are at particular risk for bullying and mental health problems. The Centers for Disease Control and Prevention’s 2021 Youth Risk Behavior survey, for instance, found that more than 1 in 3 gay, lesbian and bisexual students were bullied either on school property or online in the previous year. For about 1 in 4, the bullying was at school. Among straight students, those rates were about half as high.

When Max Ibarra was a sophomore in high school in the Chino Valley, Calif., east of Los Angeles, they endured what Max thinks of as everyday bullying from other students.

Max, who identifies as trans and nonbinary, recalled hearing snickering behind their back. In one class, they said, another student regularly threw erasers and wads of paper at them in class. In the hallway once, someone purposefully stuck out a shoulder to shove Max into the brick wall.

But what really bothers Max, now 17, is what the Chino Valley Unified School District school board did. In July 2023, the board approved a policy requiring the school to notify parents if a student asked to use a name that differed from official records, or if they asked to use pronouns or school facilities that do not align with the sex listed on the student’s birth certificate.

At the school board meeting where the policy was approved, 4-1, Max shouted objections into the microphone during the public comment period. They said that many trans students feel safe at school but not at home, and that the policy “shoves them in the closet.”

“I am tired of the idea that all parents love and support their children unconditionally. That is not true,” they yelled into the microphone. “There are evil people in this world, and some of them have children. Shocking, I know! Some prefer a dead child to a trans child.”

A spokesperson for the district declined to respond directly to Max’s assertions but said the schools have systems in place to report and respond to bullying and to address the needs of LGBTQ+ students. The district, she said, is “committed to upholding an educational setting that encourages, emboldens, and motivates scholars to become the global citizens they are meant to be.”

The policy was later put on hold by a court, and Thursday, the school board rolled back most of it. Still, Max said in an interview that the tone set by the school board remains.

“This culture of hostility and division has been festering, especially for the last three years, and its ramped up more and more each year,” Max said. “The school board has made it very clear we’re not welcome here. It’s very clear they don’t want us to exist.”

Emily Guskin and Scott Clement contributed to this report.

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The Philippines economy in 2024: Stronger for longer?

The Philippines ended 2023 on a high note, being the fastest growing economy across Southeast Asia with a growth rate of 5.6 percent—just shy of the government's target of 6.0 to 7.0 percent. 1 “National accounts,” Philippine Statistics Authority, January 31, 2024; "Philippine economic updates,” Bangko Sentral ng Pilipinas, November 16, 2023. Should projections hold, the Philippines is expected to, once again, show significant growth in 2024, demonstrating its resilience despite various global economic pressures (Exhibit 1). 2 “Economic forecast 2024,” International Monetary Fund, November 1, 2023; McKinsey analysis.

The growth in the Philippine economy in 2023 was driven by a resumption in commercial activities, public infrastructure spending, and growth in digital financial services. Most sectors grew, with transportation and storage (13 percent), construction (9 percent), and financial services (9 percent), performing the best (Exhibit 2). 3 “National accounts,” Philippine Statistics Authority, January 31, 2024. While the country's trade deficit narrowed in 2023, it remains elevated at $52 billion due to slowing global demand and geopolitical uncertainties. 4 “Highlights of the Philippine export and import statistics,” Philippine Statistics Authority, January 28, 2024. Looking ahead to 2024, the current economic forecast for the Philippines projects a GDP growth of between 5 and 6 percent.

Inflation rates are expected to temper between 3.2 and 3.6 percent in 2024 after ending 2023 at 6.0 percent, above the 2.0 to 4.0 percent target range set by the government. 5 “Nomura downgrades Philippine 2024 growth forecast,” Nomura, September 11, 2023; “IMF raises Philippine growth rate forecast,” International Monetary Fund, July 16, 2023.

For the purposes of this article, most of the statistics used for our analysis have come from a common thread of sources. These include the Central Bank of the Philippines (Bangko Sentral ng Pilipinas); the Department of Energy Philippines; the IT and Business Process Association of the Philippines (IBPAP); and the Philippines Statistics Authority.

The state of the Philippine economy across seven major sectors and themes

In the article, we explore the 2024 outlook for seven key sectors and themes, what may affect each of them in the coming year, and what could potentially unlock continued growth.

Financial services

The recovery of the financial services sector appears on track as year-on-year growth rates stabilize. 6 Philippines Statistics Authority, November 2023; McKinsey in partnership with Oxford Economics, November 2023. In 2024, this sector will likely continue to grow, though at a slower pace of about 5 percent.

Financial inclusion and digitalization are contributing to growth in this sector in 2024, even if new challenges emerge. Various factors are expected to impact this sector:

Inclusive finance: Bangko Sentral ng Pilipinas continues to invest in financial inclusion initiatives. For example, basic deposit accounts (BDAs) reached $22 million in 2023 and banking penetration improved, with the proportion of adults with formal bank accounts increasing from 29 percent in 2019 to 56 percent in 2021. 7 “Financial inclusion dashboard: First quarter 2023,” Bangko Sentral ng Pilipinas, February 6, 2024.
Digital adoption: Digital channels are expected to continue to grow, with data showing that 60 percent of adults who have a mobile phone and internet access have done a digital financial transaction. 8 “Financial inclusion dashboard: First quarter 2023,” Bangko Sentral ng Pilipinas, February 6, 2024. Businesses in this sector, however, will need to remain vigilant in navigating cybersecurity and fraud risks.
Unsecured lending growth: Growth in unsecured lending is expected to continue, but at a slower pace than the past two to three years. For example, unsecured retail lending for the banking system alone grew by 27 percent annually from 2020 to 2022. 9 “Loan accounts: As of first quarter 2023,” Bangko Sentral ng Pilipinas, February 6, 2024; "Global banking pools,” McKinsey, November 2023. Businesses in this field are, however, expected to recalibrate their risk profiling models as segments with high nonperforming loans emerge.
High interest rates: Key interest rates are expected to decline in the second half of 2024, creating more accommodating borrowing conditions that could boost wholesale and corporate loans.

Supportive frameworks have a pivotal role to play in unlocking growth in this sector to meet the ever-increasing demand from the financially underserved. For example, financial literacy programs and easier-to-access accounts—such as BDAs—are some measures that can help widen market access to financial services. Continued efforts are being made to build an open finance framework that could serve the needs of the unbanked population, as well as a unified credit scoring mechanism to increase the ability of historically under-financed segments, such as small and medium-sized enterprises (SMEs), to access formal credit. 10 “BSP launches credit scoring model,” Bangko Sentral ng Pilipinas, April 26, 2023.

Energy and Power

The outlook for the energy sector seems positive, with the potential to grow by 7 percent in 2024 as the country focuses on renewable energy generation. 11 McKinsey analysis based on input from industry experts. Currently, stakeholders are focused on increasing energy security, particularly on importing liquefied natural gas (LNG) to meet power plants’ requirements as production in one of the country’s main sources of natural gas, the Malampaya gas field, declines. 12 Myrna M. Velasco, “Malampaya gas field prod’n declines steeply in 2021,” Manila Bulletin , July 9, 2022. High global inflation and the fact that the Philippines is a net fuel importer are impacting electricity prices and the build-out of planned renewable energy projects. Recent regulatory moves to remove foreign ownership limits on exploration, development, and utilization of renewable energy resources could possibly accelerate growth in the country’s energy and power sector. 13 “RA 11659,” Department of Energy Philippines, June 8, 2023.

Gas, renewables, and transmission are potential growth drivers for the sector. Upgrading power grids so that they become more flexible and better able to cope with the intermittent electricity supply that comes with renewables will be critical as the sector pivots toward renewable energy. A recent coal moratorium may position natural gas as a transition fuel—this could stimulate exploration and production investments for new, indigenous natural gas fields, gas pipeline infrastructure, and LNG import terminal projects. 14 Philippine energy plan 2020–2040, Department of Energy Philippines, June 10, 2022; Power development plan 2020–2040 , Department of Energy Philippines, 2021. The increasing momentum of green energy auctions could facilitate the development of renewables at scale, as the country targets 35 percent share of renewables by 2030. 15 Power development plan 2020–2040 , 2022.

Growth in the healthcare industry may slow to 2.8 percent in 2024, while pharmaceuticals manufacturing is expected to rebound with 5.2 percent growth in 2024. 16 McKinsey analysis in partnership with Oxford Economics.

Healthcare demand could grow, although the quality of care may be strained as the health worker shortage is projected to increase over the next five years. 17 McKinsey analysis. The supply-and-demand gap in nursing alone is forecast to reach a shortage of approximately 90,000 nurses by 2028. 18 McKinsey analysis. Another compounding factor straining healthcare is the higher than anticipated benefit utilization and rising healthcare costs, which, while helping to meet people's healthcare budgets, may continue to drive down profitability for health insurers.

Meanwhile, pharmaceutical companies are feeling varying effects of people becoming increasingly health conscious. Consumers are using more over the counter (OTC) medication and placing more beneficial value on organic health products, such as vitamins and supplements made from natural ingredients, which could impact demand for prescription drugs. 19 “Consumer health in the Philippines 2023,” Euromonitor, October 2023.

Businesses operating in this field may end up benefiting from universal healthcare policies. If initiatives are implemented that integrate healthcare systems, rationalize copayments, attract and retain talent, and incentivize investments, they could potentially help to strengthen healthcare provision and quality.

Businesses may also need to navigate an increasingly complex landscape of diverse health needs, digitization, and price controls. Digital and data transformations are being seen to facilitate improvements in healthcare delivery and access, with leading digital health apps getting more than one million downloads. 20 Google Play Store, September 27, 2023. Digitization may create an opportunity to develop healthcare ecosystems that unify touchpoints along the patient journey and provide offline-to-online care, as well as potentially realizing cost efficiencies.

Consumer and retail

Growth in the retail and wholesale trade and consumer goods sectors is projected to remain stable in 2024, at 4 percent and 5 percent, respectively.

Inflation, however, continues to put consumers under pressure. While inflation rates may fall—predicted to reach 4 percent in 2024—commodity prices may still remain elevated in the near term, a top concern for Filipinos. 21 “IMF raises Philippine growth forecast,” July 26, 2023; “Nomura downgrades Philippines 2024 growth forecast,” September 11, 2023. In response to challenging economic conditions, 92 percent of consumers have changed their shopping behaviors, and approximately 50 percent indicate that they are switching brands or retail providers in seek of promotions and better prices. 22 “Philippines consumer pulse survey, 2023,” McKinsey, November 2023.

Online shopping has become entrenched in Filipino consumers, as they find that they get access to a wider range of products, can compare prices more easily, and can shop with more convenience. For example, a McKinsey Philippines consumer sentiment survey in 2023 found that 80 percent of respondents, on average, use online and omnichannel to purchase footwear, toys, baby supplies, apparel, and accessories. To capture the opportunity that this shift in Filipino consumer preferences brings and to unlock growth in this sector, retail organizations could turn to omnichannel strategies to seamlessly integrate online and offline channels. Businesses may need to explore investments that increase resilience across the supply chain, alongside researching and developing new products that serve emerging consumer preferences, such as that for natural ingredients and sustainable sources.

Manufacturing

Manufacturing is a key contributor to the Philippine economy, contributing approximately 19 percent of GDP in 2022, employing about 7 percent of the country’s labor force, and growing in line with GDP at approximately 6 percent between 2023 and 2024. 23 McKinsey analysis based on input from industry experts.

Some changes could be seen in 2024 that might affect the sector moving forward. The focus toward building resilient supply chains and increasing self-sufficiency is growing. The Philippines also is likely to benefit from increasing regional trade, as well as the emerging trend of nearshoring or onshoring as countries seek to make their supply chains more resilient. With semiconductors driving approximately 45 percent of Philippine exports, the transfer of knowledge and technology, as well as the development of STEM capabilities, could help attract investments into the sector and increase the relevance of the country as a manufacturing hub. 24 McKinsey analysis based on input from industry experts.

To secure growth, public and private sector support could bolster investments in R&D and upskill the labor force. In addition, strategies to attract investment may be integral to the further development of supply chain infrastructure and manufacturing bases. Government programs to enable digital transformation and R&D, along with a strategic approach to upskilling the labor force, could help boost industry innovation in line with Industry 4.0 demand. 25 Industry 4.0 is also referred to as the Fourth Industrial Revolution. Priority products to which manufacturing industries could pivot include more complex, higher value chain electronic components in the semiconductor segment; generic OTC drugs and nature-based pharmaceuticals in the pharmaceutical sector; and, for green industries, products such as EVs, batteries, solar panels, and biomass production.

Information technology business process outsourcing

The information technology business process outsourcing (IT-BPO) sector is on track to reach its long-term targets, with $38 billion in forecast revenues in 2024. 26 Khriscielle Yalao, “WHF flexibility key to achieving growth targets—IBPAP,” Manila Bulletin , January 23, 2024. Emerging innovations in service delivery and work models are being observed, which could drive further growth in the sector.

The industry continues to outperform headcount and revenue targets, shaping its position as a country leader for employment and services. 27 McKinsey analysis based in input from industry experts. Demand from global companies for offshoring is expected to increase, due to cost containment strategies and preference for Philippine IT-BPO providers. New work setups continue to emerge, ranging from remote-first to office-first, which could translate to potential net benefits. These include a 10 to 30 percent increase in employee retention; a three- to four-hour reduction in commute times; an increase in enabled talent of 350,000; and a potential reduction in greenhouse gas emissions of 1.4 to 1.5 million tons of CO 2 per year. 28 McKinsey analysis based in input from industry experts. It is becoming increasingly more important that the IT-BPO sector adapts to new technologies as businesses begin to harness automation and generative AI (gen AI) to unlock productivity.

Talent and technology are clear areas where growth in this sector can be unlocked. The growing complexity of offshoring requirements necessitates building a proper talent hub to help bridge employee gaps and better match local talent to employers’ needs. Businesses in the industry could explore developing facilities and digital infrastructure to enable industry expansion outside the metros, especially in future “digital cities” nationwide. Introducing new service areas could capture latent demand from existing clients with evolving needs as well as unserved clients. BPO centers could explore the potential of offering higher-value services by cultivating technology-focused capabilities, such as using gen AI to unlock revenue, deliver sales excellence, and reduce general administrative costs.

Sustainability

The Philippines is considered to be the fourth most vulnerable country to climate change in the world as, due to its geographic location, the country has a higher risk of exposure to natural disasters, such as rising sea levels. 29 “The Philippines has been ranked the fourth most vulnerable country to climate change,” Global Climate Risk Index, January 2021. Approximately $3.2 billion, on average, in economic loss could occur annually because of natural disasters over the next five decades, translating to up to 7 to 8 percent of the country’s nominal GDP. 30 “The Philippines has been ranked the fourth most vulnerable country to climate change,” Global Climate Risk Index, January 2021.

The Philippines could capitalize on five green growth opportunities to operate in global value chains and catalyze growth for the nation:

Renewable energy: The country could aim to generate 50 percent of its energy from renewables by 2040, building on its high renewable energy potential and the declining cost of producing renewable energy.
Solar photovoltaic (PV) manufacturing: More than a twofold increase in annual output from 2023 to 2030 could be achieved, enabled by lower production costs.
Battery production: The Philippines could aim for a $1.5 billion domestic market by 2030, capitalizing on its vast nickel reserves (the second largest globally). 31 “MineSpans,” McKinsey, November 2023.
Electric mobility: Electric vehicles could account for 15 percent of the country’s vehicle sales by 2030 (from less than 1 percent currently), driven by incentives, local distribution, and charging infrastructure. 32 McKinsey analysis based on input from industry experts.
Nature-based solutions: The country’s largely untapped total abatement potential could reach up to 200 to 300 metric tons of CO 2 , enabled by its biodiversity and strong demand.

The Philippine economy: Three scenarios for growth

Having grown faster than other economies in Southeast Asia in 2023 to end the year with 5.6 percent growth, the Philippines can expect a similarly healthy growth outlook for 2024. Based on our analysis, there are three potential scenarios for the country’s growth. 33 McKinsey analysis in partnership with Oxford Economics.

Slower growth: The first scenario projects GDP growth of 4.8 percent if there are challenging conditions—such as declining trade and accelerated inflation—which could keep key policy rates high at about 6.5 percent and dampen private consumption, leading to slower long-term growth.

Soft landing: The second scenario projects GDP growth of 5.2 percent if inflation moderates and global conditions turn out to be largely favorable due to a stable investment environment and regional trade demand.

Accelerated growth: In the third scenario, GDP growth is projected to reach 6.1 percent if inflation slows and public policies accommodate aspects such as loosening key policy rates and offering incentive programs to boost productivity.

Focusing on factors that could unlock growth in its seven critical sectors and themes, while adapting to the macro-economic scenario that plays out, would allow the Philippines to materialize its growth potential in 2024 and take steps towards achieving longer-term, sustainable economic growth.

Jon Canto is a partner in McKinsey’s Manila office, where Frauke Renz is an associate partner, and Vicah Villanueva is a consultant.

The authors wish to thank Charlene Chua, Charlie del Rosario, Ryan delos Reyes, Debadrita Dhara, Evelyn C. Fong, Krzysztof Kwiatkowski, Frances Lee, Aaron Ong, and Liane Tan for their contributions to this article.

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What does 2023 hold for the Philippines’ economy?

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On the verge of a digital banking revolution in the Philippines

Industries Overview

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The US healthcare industry is massive, with healthcare spending accounting for over 18.3% of US GDP in 2021.
We break down the industry’s various sectors and recent trends hoping to reduce costs while improving care.
Do you work in the healthcare industry? Get business insights on the latest tech innovations, market trends, and your competitors with data-driven research.

The US healthcare industry is massive, and is continuing to grow as the population swells. Many different types of companies and healthcare institutions work together to provide patient satisfaction and a better quality of care—but sometimes it comes at a large cost.

70% of US adults believe that mental healthcare is not handled well, according to a survey conducted by NORC at the University of Chicago. - Insider Intelligence

Could new digital health startups help reduce costs while improving health care services? Insider Intelligence examines the healthcare industry, its latest trends, and what the future has in store.

US Healthcare Industry Size & Spending

The global healthcare market will reach $665.37 billion by 2028, according to Verified Market Research. US national healthcare expenditure reached $4.3 trillion in 2021, or $12,914 per person, and is estimated to reach $6.2 trillion by 2028, per the Centers for Medicare and Medicaid Services.

US healthcare is more expensive than most countries. According to the Commonwealth Fund, the US spent nearly 16.8% of gross domestic product (GDP) on healthcare in 2019. Germany was the second-highest ranking country, spending 11.7%, followed by Switzerland, spending 11.3%.

Deloitte estimates that, if the current trajectory continues, health spending will triple to nearly $12 trillion by 2040, or 26% of the GDP. The consulting firm also suggests that this growth is largely driven by inequities in the US healthcare system. Unnecessary healthcare spending that stems from structural inequities and biases, specifically related to race, gender, and socioeconomic status, currently costs the country $320 billion.

Another driver of these high costs is healthcare companies’ adoption of emerging health-focused technology. US healthcare providers and facilities spent $17.9 billion on cloud-based technologies in 2022—a figure that is expected to jump to $29.15 billion in 2026.

To offset costs, healthcare providers are leveraging the increase in consumers who want to play a more active role in monitoring their own health by encouraging tech that promotes vital tracking, early detection, and prevention of disease. Specifically, remote patient monitoring (RPM) tools, which enable a continuous stream of real-time health data between patients and their doctors, will account for much of this savings.

Demand for RPM will increase, but a lack of a broadband connection will still be an issue for many patients, especially those who are elderly and/or live in rural areas. - Insider Intelligence

In 2023, the RPM space in 2023 will be rife with players, from providers to retailers. In fact, some 57% of provider organizations already use RPM to monitor patients’ vital signs at home, according to a January 2022 survey conducted by Sage Growth Partners on behalf of Rhythm. And, by 2024, over 75% of US medical practices will be leveraging the technology.

Like what you’re reading? Click here to learn more about Insider Intelligence’s leading Health research.

US Healthcare Sectors

Healthcare involves many parties working together. From healthcare staffing and administration to providers and patient care, the market is buoyed by a variety of different workers and technologies. Some healthcare sectors include:

Health insurance
Healthcare marketing
Pharmaceuticals
Healthcare tech
Health administration

US Healthcare Industry Trends

House calls are making a comeback—in a way. Insurers and retailers are now buying home health companies to expand into in-home care. Remote patient monitoring (RPM) and at-home diagnostic tests are helping to boost these efforts. Up to $265 billion in care services for traditional Medicare and Medicare Advantage (MA) beneficiaries could migrate from traditional facilities to the home by 2025, per McKinsey & Company. Expect more big brands to move in.

Retailers and Insurers

Providing in-home care can reduce costs related to emergency room visits, decrease hospital readmissions, and even speed recovery time. Over the past year, big companies—including retailers like Amazon—have spent billions to stake a claim in the home healthcare market.

Baby boomers looking to “age in place” will be prime candidates for in-home healthcare. By 2030, all of the nearly 70 million boomers (now 58 to 76 years old) will be 65 or older, with the oldest close to 85. Most will be using some form of Medicare for their health coverage.

Demand for convenience and distanced care continues, and RPM adoption will only increase post-pandemic. We estimate there will be 70.6 million RPM users in the US by 2025, up 56.5% from 2022. In three years, more than one-quarter of the US population will be regularly using a device that remotely tracks or collects their well-being or medical data for their doctors to assess.

Healthcare organizations are working to better provide support services to patients. - Insider Intelligence

At-Home Tests

The do-it-yourself healthcare market is booming. While sales of COVID-19 tests are waning, manufacturers and providers are rolling out other types of at-home tests, including those for sexually transmitted diseases—now considered an “out-of-control” situation in the US.

The global home diagnostics market was estimated at $5.42 billion in 2021 and is expected to reach $8.15 billion by 2030, according to Precedence Research.

Mental Health Coverage

Mental health benefits are now a priority for both employees and employers. Offering virtual mental health care programs helps to mitigate employee “burnout” and keep costs low.

Rising prescription drug costs and treating chronic health conditions, however, are adding pressure on employers every year. At the same time, inflation has led 13% of adults to cut healthcare costs completely , per an August 2022 First Insight report.

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Facility for Rare Isotope Beams

At michigan state university, winners of 2023 frib achievement award for early career researchers named.

14 July 2023

The FRIB Users Organization Executive Committee and the FRIB Theory Alliance Executive Board have announced the winners of the 2023 FRIB Achievement Award for Early Career Researchers . Katharina Domnanich, assistant professor of chemistry at FRIB and in the MSU Department of Chemistry, is the recipient of the 2023 experimental award. Kyle Godbey, research assistant professor at FRIB, is the recipient of the 2023 theory award.

The selection committee stated:

Dr. Katharina Domnanich’s research focuses on Isotope Harvesting at the Facility for Rare Isotope Beams. Dr. Domnanich made critical contributions to isotope harvesting techniques and technologies that will enable research into new therapies for cancer treatment, direct measurements of nuclear reactions on short-lived nuclei important for nuclear astrophysics, and multi-user capabilities at FRIB. Additionally, her work on the radiolysis of the water in the FRIB beam dump will enable safe high-power operations, which will benefit the entire user community. Dr. Domnanich’s impressive scientific leadership was noted by all of the committee members.

Dr. Kyle Godbey’s research is on the dynamics of heavy nuclei, with an emphasis on fission and reactions, particularly fusion and quasifission. His work to relate these processes to nuclear structure makes his connection with FRIB science particularly strong. It also places him at the center of the community-wide effort to quantify the uncertainty in predictions of nuclear observables. Only three years from his PhD, he is already the first author of seven papers (and a part of 13 more), four of which have received more than 20 citations. In addition, he has published a useful online book on quantum computing, advises four students at MSU, and is the lead organizer of this year’s FRIB Theory Alliance Summer School, on uncertainty quantification and emulator development. Though it did not affect our decision making, this influential scientific service supplements Kyle Godbey’s first-rate research in a way that makes him a worthy recipient of the 2023 FRIB Achievement Award for Early Career Researchers.

Katharina Domnanich

Domnanich’s research focuses on isotope harvesting, a new area of opportunity for researchers. During routine operation for its nuclear physics mission—without interfering with FRIB’s primary users—extra, unused isotopes can be “harvested” using additional tools and infrastructure. These by-product radionuclides are of immense value to society and science. The collection of these exotic radionuclides from the cooling-water loop became known as “isotope harvesting,” and it was successfully tested at FRIB’s predecessor facility, the National Superconducting Cyclotron Laboratory. To extend the spectrum of pure radioisotopes that are accessible via isotope harvesting, Domnanich said scientists envision using mass separation. In particular, her focus will be directed toward radioisotopes, which are of interest for scientific applications, like neutron cross-section studies or nuclear medicine.

Domnanich said that in recent years, the increasing demand for non-standard radionuclides in the U.S. is outstripping supply capabilities. These radionuclides are indispensable for a broad range of applied and fundamental nuclear science applications, including nuclear medicine, stockpile stewardship, and fundamental physics. She said the collection from FRIB’s aqueous cooling-water stream represents a novel source that can develop into an important asset to meet our growing isotope demands.

“FRIB is a world-leading facility for research with the rarest isotopes and provides an unparalleled opportunity to study and collaborate with experts in nuclear physics and chemistry,” she said. “The isotope harvesting and mass-separation capabilities are one-of-a-kind setups that will contribute to pushing the limits of current knowledge.”

Domnanich earned a bachelor’s degree in medicinal chemistry and pharmaceutical sciences from the Dublin Institute of Technology in Ireland, a master’s degree in chemistry from the University of Vienna in Austria, and a PhD in chemistry from the University of Bern in Switzerland.

Kyle Godbey

Godbey’s research explores nuclear physics through the use of microscopic models. Godbey’s primary focus is investigating the dynamics of heavy nuclei and how they play a role in phenomena at scales spanning from nuclear reactions to neutron stars. This work sits at the intersection of nuclear theory, computational statistics, and high-performance computing and places a strong emphasis on open science principles and accessibility. In addition to his work in nuclear physics, he is also involved in a number of complementary efforts to develop tools and techniques in computing and statistics.

While he has many open lines of research, Godbey said he is excited about his work in heavy-ion fusion and fission. Atomic nuclei are incredibly complex, self-bound quantum systems. If scientists exploit the state-of-the-art in predictive theories, he said, they can learn a lot about their properties by studying how they behave in time. Godbey said he likes to study reactions between heavy-nuclei at the edge of stability, and he said he suspects that there's going to be very interesting physics to uncover as scientists start to probe deeper into the as-of-yet unknown regions of the nuclear landscape that FRIB will open up.

“Both FRIB's scientific users and the frequent visitors that come by each year are such a wellspring of inspiration and a source of many of the high-impact projects that I've been involved with thus far,” he said. “I'd like to highlight the participants and students that attend the various workshops and summer schools in particular—they are always so excited to collaborate and get involved with FRIB science, and I frequently hear that these sorts of programs convince a lot of people to continue in this field of physics. The incredible rates of exotic nuclei will have a more direct impact on my day-to-day physics studies, primarily because the data that I need to better inform my theoretical models simply cannot be obtained anywhere else. Every facet of my research program in nuclear structure and reactions will be greatly elevated by the experimental research being done at FRIB and the broader campus community also contribute a great deal in the areas of high performance computing, applied mathematics, and statistics.”

Godbey earned a bachelor’s degree in physics with a minor in computer science from Berea College and a master’s degree and PhD (both in physics) from Vanderbilt University .

The FRIB Achievement Award for Early Career Researchers recognizes outstanding original contributions to the field of nuclear physics through work at or relating to FRIB, performed by scientists early in their careers.

The recipients will present their work during the plenary session at the annual Low Energy Community Meeting and receive a stipend to support their participation.

Michigan State University (MSU) operates FRIB as a user facility for the Office of Nuclear Physics in the U.S. Department of Energy Office of Science. Hosting what is designed to be the most powerful heavy-ion accelerator, FRIB will enable scientists to make discoveries about the properties of rare isotopes in order to better understand the physics of nuclei, nuclear astrophysics, fundamental interactions, and applications for society, including in medicine, homeland security, and industry.

The U.S. Department of Energy Isotope R&D and Production Program (DOE Isotope Program) supports isotope harvesting at FRIB. MSU operates FRIB as a user facility for the Office of Nuclear Physics in the U.S. Department of Energy Office of Science , supporting the mission of the DOE-SC Office of Nuclear Physics.

The U.S. Department of Energy Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of today’s most pressing challenges. For more information, visit energy.gov/science .

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Additional statistics project examples: To show the study of AP statistics project ideas, you need to offer arguments based on the evidence, perform research, and analyze the issues. You can write a statistics project based on alcohol advertisements and their effect on younger people of these ads. Statistics Final Project Ideas
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Have a look at some good topics for statistics projects:-1. Research the average height and physics of basketball players. 2. Birth and death rate in a specific city or country. 3. Study on the obesity rate of children and adults in the USA. 4. The growth rate of China in the past few years 5. Major causes of injury in Football
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500+ Statistics Research Topics. January 4, 2024. by Muhammad Hassan. Statistics is a branch of mathematics that deals with the collection, analysis, interpretation, presentation, and organization of data. It is a fundamental tool used in various fields such as business, social sciences, engineering, healthcare, and many more.
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Researchers and statistics teachers are often tasked with writing an article or paper on a given stats project idea. One of the most crucial things in writing an outstanding and well-composed statistics research project, paper, or essay is to come up with a very interesting topic that will captivate your reader's minds and provoke their thoughts.
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Many people enjoy having a regular size, 52 g, or a king size, 96 g, Payday candy bar as a snack. Our group wanted to see what percent of Payday candy bars are nuts. In addition, we wanted to know how the size of the candy bar would affect the amount of nuts. The population that we sampled was all Payday candy bars weighing both 52 g and 96 g.
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Project Ideas. Here are some generic project ideas that you can use to jump start the students brainstorming process. In each case, several factors are given that might affect the dependent variable. Students could use one or more of the factors depending on the type of statistical analysis you want them to do.
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This is more about gathering and organizing data than statistics, but I've often thought that it would be great to have a "US Version" of David MacKay's excellent Sustainable Energy - without the hot air.Its numbers and examples of things related to energy usage are UK-based, and especially when I point to this book when teaching, it would be good to have parallel data conveniently ...
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Here are some intriguing project ideas: Study habits vs. academic performance: Survey students about their study habits and analyze how it relates to their grades. Marketing strategy effectiveness research: Collect sales data from various marketing campaigns and compare their impact on revenue.
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In addition to his work in nuclear physics, he is also involved in a number of complementary efforts to develop tools and techniques in computing and statistics. While he has many open lines of research, Godbey said he is excited about his work in heavy-ion fusion and fission. Atomic nuclei are incredibly complex, self-bound quantum systems.

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