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• PhD Level Statistics Tutors

Award-Winning PhD Level Statistics Tutors

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Private PhD Level Statistics Tutoring

Our interview process, stringent qualifications, and background screening ensure that only the best PhD Level Statistics tutors work with Varsity Tutors. To assure a successful experience, you're paired with one of these qualified tutors by an expert director - and we stand behind that match with our money-back guarantee.

Receive personally tailored PhD Level Statistics lessons from exceptional tutors in a one-on-one setting. We help you connect with the best tutor for your particular needs while offering flexible scheduling to fit your busy life.

Whether you're pursuing a career in data science in astronomy, computational biology, economics, applied statistics, biostatistics, or any of many other disciplines that allow you to perform high-level data analysis, you'll have many more career options if you earn your PhD in addition to or instead of your master's degree. If your goal is to work in academia or to do research in the government or private industry, you'll likely need a PhD in statistics. One thing to remember is that asking for help in a difficult field of study is a strength, and shows your determination to do your best work. Varsity Tutors can connect you with PhD-level statistics tutoring to help you.

PhD-level statistics tutoring is available to help you with all the in-depth topics you'll be studying for your doctoral program, including:

• Advanced applied and theoretical statistics
• Models in operations research
• Linear programming
• Time series and multivariate analysis
• Bayesian statistics and generalized linear models

This is only a sampling of the interesting, though complex, subjects your personal statistics tutor can help you with. You've been at this for awhile, and if you've been searching terms like "PhD-level statistics tutoring near me," you're already aware of the complexity of this subject, and the value of working with somebody who has the knowledge and experience to help you as you study, run tests, and write papers.

PhD-level statistics tutoring can do that for you. Your tutor may have direct experience working at this high level, and can understand the things you are struggling with. They may also have just the solution for you, based on your particular needs and strengths, as well as your individual goals. Your private PhD statistics tutor may help you set up a study schedule that will provide you with enough time to study, complete assignments and projects, and do the work necessary to finish your degree. Your tutor may help you set incremental goals as you work on your thesis, so that you don't find yourself with only an outline, and a month away from presenting it to the committee.

Though you may have gained these kinds of skills in your years of academia so far, it can be comforting and reassuring to have somebody who can offer encouragement and support in addition to academic assistance. Contact us at Varsity Tutors to get connected with graduate statistics tutoring today. We hope to hear from you!

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Statistics Tutoring with PhD & MBA Tutors

We provide statistics tutoring for a variety of statistics courses including Managerial Statistics , Statistics for Managers, Data Analysis & Statistics, Statistics Concepts & Methods, etc . Read on to find out how our statistics tutors can assist you with live online one-on-one statistics tutoring so you truly understand statistics and data analysis.

Common topics covered by our statistics tutors

Our statistics tutors provide live statistics tutoring in the statistics topics covered in an MBA, CPA or CFA program including:

• Using Microsoft Excel for data analysis
• Graphing and describing data in tables and charts
• Descriptive measures
• Probability and business decisions
• Probability distributions (discrete probability distributions & continuous probability distributions)
• Time series forecasting
• Decision making
• Confidence interval estimation (with known and unknown standard deviations)
• Hypothesis testing (with the z test approach, t test approach, p value approach, one tail test, two tail test, etc.)
• Two sample tests
• Analysis of variance or ANOVA
• Chi Square tests and other non parametric tests
• Simple linear regression
• Multiple regression
• Regression model building

This is a sample list only. We will be happy to provide you statistics tutoring in the topics you need assistance with.

Textbooks used by our statistics tutoring team

Our statistics tutors are well-versed in statistics and can tutor students using any statistics and data analysis textbook. In our experience, the most popular tutoring requests have been for:

• Albright, Winston and Zappe’s Data Analysis and Decision Making with Microsoft Excel
• Anderson, Sweeney, Williams and Freeman’s Statistics for Business and Economics
• Levine, Stephan, Krehbiel and Berenson’s  Business Statistics: A First Course
• Anderson, Sweeney, Williams, Camm and Martin’s Quantitative Methods for Business
• Bowerman & O’Connell’s Business Statistics in Practice
• Bertsimas and Freund’s Data, Models, and Decisions: The Fundamentals of Management Science
• Schleifer and Bell’s Data Analysis, Regression, and Forecasting
• Groebner, Shannon, Fry, and Smith, A Course in Business Statistic
• McClave, Benson, and Sincich, Statistics for Business and Economics
• Golnick and Smith, The Cartoon Guide to Statistics

This is only a sample list of the statistics textbooks our statistics tutoring team has used to tutor students . Your statistics tutor will use the textbook prescribed in your statistics course or your professor’s notes to assist you.

Backgrounds & qualifications of our statistics tutors

Our statistics tutors are PhDs, MBAs and CPAs.  Our tutors are typically working professionals in various organizations and so prefer not to post their profiles online. We will be happy to provide you your statistics tutor’s background before you are tutored by GraduateTutor.com.

Statistics courses come in “different shapes, sizes and styles”

All universities and business programs teach statistics.  However, they set different standards, focus on different topics and use a wide variety of course names.  A list of common courses / titles is provided below:

• Data Analysis & Statistics
• Statistics Concepts & Methods
• Business Statistics
• Statistics and Management
• Principles of Statistics & Measurements
• Managerial Statistics
• Statistics for Managers

We will be happy to assist you with statistics tutoring for your statistics course whatever be its name!

Statistics courses we have provided statistics tutoring in

A sample list of courses we have tutored students in include:

• MBAA 603: Business Statistics, Loyola Maryland University
• 6N:216 Data and Decisions University of Iowa
• ITOM Business Statistics Cox School of Business
• EXP 420 – Managerial Decision Analysis, Simon Graduate School, Rochester
• BA 575: Statistics For Business, Schiller International University
• BUS 550E: Decision Analysis, Emory
• B6014 Managerial statistics, Columbia
• DG7820 Statistical reasoning, Fordham
• Statistics for management, Cornell MBA
• OMS503 Statistical methods, Cleveland
• Managerial decision making, Cornell MBA
• BUS 550Y Data/decision analytics, Emory
• GM533 Applied Managerial Statistics, Keller
• B8899 Applied Regression Analysis, Columbia GSB MBB & EMBA
• Managerial Decision Making, Chicago Booth
• Managerial Statistics, Chicago Booth
• GM530 Managerial Decision Making, Keller
• B7014 Managerial Statistics, Columbia
• B01 Statistics and Data Analysis, NYU Stern
• 465: Quantitative Methods for Managers
• B90 Regression and Multivariate Data Analysis, NYU-Stern, New York City
• 463: Data Analysis and Management Decisions under Uncertainty,  UCLA
• B90 Forecasting Time Series Data, NYU – Stern
• 15.060 Data, Models, and Decisions, MIT
• B90 Mathematics of Investment, NYU-Stern
• C22 Statistics for Business Control EMBA
• Data Analysis, Statistics & Decision Making
• B90.3302 Statistical Inference and Regression Analysis, NYU-Stern

This is only a sample list of statistics courses we have covered in the recent past. We will be happy to provide you statistics tutoring for your specific statistics class.

Email or call us or simply fill out the sign-up form below to start live one-on-one statistics tutoring.

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Statistics and associated software and techniques: r, spss, excel and other software on demand

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Abdallah is amazing to work with, he is very patient and flexible especially on my busy schedules. He takes his time to understand the topics I have questions with and make sure that I understand it. He is also very smart and knows what he is...

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Professor Robert is true gentleman and has exensive knowledge regarding multiple subjects

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I’m so happy with her skills. She’s was so understanding and patient with me. I would recommend her to anyone who needs a tutor.

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Provide clear explanation of the topics and ensure that all the relevant information is covered.

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The average price of Statistics  lessons is $14.

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To become a statistician, you typically need a strong educational background in mathematics and statistics, as well as relevant experience. Here are some of the qualifications and skills that are typically required:

Education: A bachelor's degree in statistics, mathematics, or a related field is typically required to become a statistician. However, many positions may require a master's or doctoral degree in statistics, data science or a related field.

Strong Mathematical and Analytical Skills: Statisticians must have a solid foundation in mathematics and analytical thinking. They must be able to apply mathematical and statistical techniques to real-world problems and data.

Knowledge of Statistics Software: Statisticians should be familiar with software packages that are commonly used in the field, such as R, SAS, or Python.

Strong communication skills: Statisticians must be able to communicate complex statistical concepts and findings to non-experts.

Attention to detail: Statisticians must be detail-oriented, as small errors can lead to incorrect results.

Industry-specific knowledge: Statisticians may need to have knowledge of specific industries, such as healthcare, finance, or environmental science, in order to understand and analyze the data relevant to those fields.

Professional certification: Professional certifications such as the Certified Statistician (CStat) offered by the Royal Statistical Society or the Accredited Professional Statistician (PStat) offered by the American Statistical Association may be beneficial in demonstrating expertise and advancing one's career in the field.

On Superprof, many of our Statistics tutors offer online tuition.

To find online courses, just select the webcam filter in the search engine to see the available tutors offering online courses in your desired subject. 

73,047 tutors are currently available to give Statistics lessons near you.

You can browse the different tutor profiles to find one that suits you best.

Find your tutor from among 73,047 profiles .

From a sample of 10,094  tutors, students rated their private tutors 5 out 5.

If you have any issues or questions, our customer service team is available to help you.

You can view tutor ratings by  consulting the reviews page .

Gain the statistical skills employers seek. Join our Statistics tutoring classes now!

Statistics for success in business, academia, and beyond with the help of a Stats tutor

Ready to conquer statistics? Our Statistics math class make it easy and fun!

From beginners to experts, our statistics tutors have something for everyone, learn statistics in the us.

The United States is home to some of the world's largest corporations. Its economic state causes a ripple effect throughout the global market. This is why a large number of students in the country are so drawn to business studies.

One of the crucial subjects taught in business school is statistics. Statistics helps businesses evaluate their finances and make data-driven decisions. Unfortunately, the subject can be perplexing for most, as the plethora of charts and figures can be especially daunting to look at.

Fortunately, there are reliable learning platforms like Superprof providing a range of proficient statistic tutors for business students and learners.

How Do Statistics Affect Our Daily Life?

Considering the complexities of statistics, many people wonder why they are studying the subject and what benefits it would bring to their careers. To prove the importance of statistics in daily life, here is a list of job scopes you can secure by studying statistics.

Statistics in Economics

Statistics teaches you to compile, disseminate, process, and analyze data efficiently. This enables the government and other important sectors of the country to make decisions based on statistical evidence. Moreover, since economics plays a crucial role in our daily lives, statistics are also vital in our everyday operations.

Statistics in Nursing

Some may find it hard to believe, but nurses and other paramedical staff rely heavily on statistics. Having a strong grasp on the manipulation and calculation of data helps the medical staff to identify the pattern of diseases and asses the sign and symptoms. Moreover, it helps medical attendants to keep track of their patient's medication and other records.

Statistics in Psychology

It might be hard for some to digest, but statistics are helpful in psychology. Pie charts, bar graphs, and other statistical tools help psychologists visualize their jobs' abstract elements. For instance, by making scatterplots, psychologists can identify their clientele's progress. Furthermore, they can also determine the right approach for the client by looking at the graphical representation of their exhibited pattern.

Statistics in Cryptocurrency

Many businesses have invested in cryptocurrency due to the concept of decentralized money. However, while cryptocurrency intrigues firms, it also makes them skeptical. This is because anything can go wrong with the investment. For example, the value of cryptocurrency can plummet unexpectedly. Considering the situation, cryptocurrency investment relies on a statistical operation. By applying statistical methods, individuals can foresee a downfall of a cryptocurrency.

Statistics in Education

Statistics is a crucial part of our education system. Aside from helping teachers keep everything on record and analyze their students' progress, statistics also enable them to tailor their techniques for each student.

Since intelligence, mental capacity, and academic proclivity differ greatly from child to child, teachers should comprehend and provide guidance based on each student's ability. Statistics are extremely useful in this regard because they allow teachers to see which of their teaching techniques apply to which student.

Why Do We Need Statistics?

Statistics is all about compiling and analyzing. As data collection is required in all research, statistics are essential in every organization. Having said that, unscrupulous data analysis is the death of institutions. It can cause them to draw erroneous conclusions and make reckless decisions. This is where statistics come to the rescue. It helps businesses to draw accurate conclusions and make informed decisions.

Learn Statistics with Superprof

Statistics, in a nutshell, is a study of numbers and their analysis. It helps people and organizations achieve their goals and avoid making unwarranted conclusions. So educate yourself in statistics and pave your way to great career choices.

Superprof offers an array of qualified statistic tutors who can help you practice and learn statistics online and in person. So wait no more and get onboard!

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I am a professional offering tutoring services in the fields of applied statistics, theoretical statistics, probability theory, stochastic processes, econometrics, biostatistics, actuarial science and mathematical finance. I hold a PhD in Statistics and a PhD Minor in Finance from Stanford University. During my five years at Stanford I taught more than ten undergraduate, master's level and PhD level statistics and probability courses. After graduation I moved to New York and, for more than a decade, I have been working in the industry focusing on projects in data mining, time series analysis, factor analysis, computational statistics, stochastic optimization, derivatives pricing and systematic trading. Equally importantly, I have tutored students and business professionals in all areas of statistics and quantitative finance for the last eight years. I have consulted researchers in medical, social and economic sciences regarding statistical aspects of their research for ten years. I help with exams, assignments, presentations, literature review, theoretical research, programming projects and data analysis in any of the major statistical packages (R / R Studio, Stata, SPSS, Matlab, SAS, JMP, Minitab, EViews, Python). As my experience shows, I work with all types of clients, from college students to full professors in other fields. Typically, I meet in Manhattan or tutor via Skype or e-mail if the client is far from New York. In Skype there is an option allowing one to see my desktop. One can see which buttons I click, where my mouse moves, which commands I type, how I perform data analysis, how I derive formulas, and so on. In the past I have tutored clients in New York, Long Island, Boston, Philadelphia, Baltimore, Washington, Pittsburgh, Chicago, Orlando, Miami, Austin, Houston, Dallas, Phoenix, San Diego, Los Angeles, San Jose, San Francisco, Seattle, Vancouver, Montreal, Toronto, London, Cambridge, Edinburgh, Utrecht, Doha, Singapore, Perth, Adelaide, Melbourne, Sydney, Brisbane and so on. TYPES OF SERVICE

1] Tutoring on the Hourly Basis

This includes preparation for exams and presentations, work on assignments, coaching for extended business related projects, sessions to improve overall understanding of the material, and so on. The minimum duration of a session is 2 hours.

This includes data analysis, assignments, review of articles and books, theoretical research, development of infrastructure for business and academic needs, answers to specific questions via e-mail, and so on. Please make sure to check out examples of the projects I have done in the past.

This is a mixture of services 1 and 2 spanning months, typically. I help you rephrase research objectives and choose appropriate statistical methodology. I perform the data analysis in the software of your choice: R, Matlab, SPSS, Stata, SAS, JMP, EViews, Minitab or Python. Alternatively, I guide you through performing the analysis yourself and help you interpret the results. I navigate your correspondence with the scientific adviser to make sure that he understands what you have done, you understand what he wants and he gives you only the tasks / ideas that you can handle. I prepare you for each public appearance, including the dissertation defense... You may want to read the dissertation tips .

I prepare study materials, homework problems and data-driven projects for you. You read the materials and do the projects on your own timing. After that, we meet face to face or in Skype. I check the results of your work and answer the list of questions you have prepared. I explain how to approach several selected tasks. After that, I give you a new batch of study materials and homework problems. The cycle repeats itself... This option allows you to improve your knowledge relatively cheaply, as you are not paying for the time when I am not around.

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• EViews Tutorial , IHS Global
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Statistics Tutoring

Statistics is a subject many high school and college students find particularly difficult. In U.S. high schools, outside of specific classes such as AP statistics, it’s a topic often left uncovered in many mathematics curriculums. As a result, when college students start encountering statistics courses, they can seem generally very difficult to comprehend.

Many of our statistics tutors have or are working on PhDs.  While some focus on younger students, others prefer the challenge of helping PhD candidates with advanced research. All are strong communicators, capable of breaking down complex concepts with a focus on teaching the core skills you need to learn while also recognizing that you have near-term homework to complete and quizzes and tests to prepare for.

We help with conceptual classes, as well as classes requiring the use of programming languages such as STATA, SPSS, R, SAS, and more. 

Over the past several years, we’ve helped statistics students succeed in:

• AP statistics
• Most college level statistics classes covering foundational concepts like probability theory
• Linear regression analysis and predictive modeling
• Applied statistics for: Business classes (i.e., Statistics for Marketing Research), Healthcare, and more
• Advanced statistical support for graduate students doing original research in various areas
• Forecasting and modeling for data science students in master's and MBA programs

Akhtar is a good example of one of our experienced statistics tutors:

• Bachelor's in Statistics, 2008
• MS, Statistics, 2010, University of North Carolina
• PhD Candidate, Bio-statistics, University of North Carolina
• Taught undergraduate statistics for 4 years
• Currently a graduate teaching assistant 

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PhD in Statistics

Phd in statistics program.

The PhD in Statistics prepares students professional leadership in statistical research, teaching and collaboration as faculty at colleges and universities and as researchers at government institutions or in the private sector.

Coursework Requirements

MS in Statistics

Qualifying, Prelim, and Final Exams

Review and Advisory

Travel Funding Policy

PhD Student Handbook

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Qualifications

• Doctorate/PhD in Economics and Finance, University of Cambridge
• MSc Economics, London School of Economics (LSE)
• BSc Economics and Econometrics, University of Nottingham

Professional experience:

• 28+ publications in leading Economics and Finance journals
• Reviewer for international peer-reviewed journals
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Teaching experience: UG and PG mentor and faculty positions at European University Institute, University of Kent, London School of Economics (LSE).

Years taught : over 15 years of teaching and supervision at UG, PG and PhD levels.

Supervision experience: 25+ UG, PG and PhD supervision.

Financial & Applied Mathematics Tutor and University Lecturer (DPhil, MSci , BSc)

• Doctorate/DPhil in Financial Mathematics, Mathematical Institute, University of Oxford
• BSc/MSci, Mathematics, University College London
• Experienced Maths tutor UCAS/ University admission for Oxford University & University of Cambridge entrance exams- MAT, STEP I, II & III
• University mentor for research scholars and staff

Teaching experience: Academic Tutor and project supervisor for UG and PG students from University of Oxford, University of London and Stanford University.

Years taught : over 8 years of teaching and supervision for UG and PG level.

Supervision experience: 10+ UG and PG supervision.

English Literature and  Language Tutor & University L ecturer (PhD, MA, BA)

• Doctorate/PhD English Literature, University of St Andrews
• MA English, Queen Mary, University of London
• BA (Hons) English, Goldsmiths, University of London

Professional experience: 15+ peer reviewed publications and speaker for over 50+ conferences.

Teaching experience: Module convenor and  faculty positions at University of Reading, University of Bristol and University of Manchester.

Years taught : over 15 years of teaching at university level.

Supervision experience: 25+ UG, PG supervision and ongoing. 3 PhD students.

International relations & Politics Tutor and University Lecturer (PhD, MA, BA)

• Doctorate/PhD in International relations and Politics, SOAS, University of London
• MA Politics, University of Manchester
• BA, Politics & International relations, University of Westminster
• Policy consultant, United Nations and major global charities
• Author of 18+ peer-reviewed journals and articles

Teaching experience: Tutor and supervisor for UG and PG students from Center for European Integration Studies, Germany, University of Westminster and University of London.

Years taught : over 10 years of teaching and supervision at UG and PG level.

Supervision experience: 18+ UG and PG supervision.

English Language & Linguistics Tutor and University Lecturer (PhD, MA, BA)

• Doctorate/PhD English Linguistics and language research, University College London
• MA Applied Linguistics, University of London
• BA Linguistics, SOAS, University of London
• TESOL Certificate, Trinity College London, UK
• 14+ peer reviewed publications and over 20 invited lectures and plenaries
• Peer-reviewer, the Linguistics journal

Teaching experience: Faculty positions at University of International Studies, Kingston University and University College London (UCL).

Years taught : 12 years of teaching and supervision at UG, PG and PhD levels.

Supervision experience: 20+ UG and PG supervision and 2 PhD students (ongoing).

Art History Tutor and University Lecturer (PhD , MA, BA)

• Doctorate/PhD in Art History, University of Arts London
• MA, Art History, Courtauld Institute of Art, University of London
• BA, Utrecht University
• Curator and Art historian for various national and international museums and galleries
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Teaching experience: Having taught UG and PG students from University of Arts London, Middlesex University, Sotheby’s Institute of Art  and University of Heidelberg.

Years taught : over 9 years of teaching  and supervision at UG, PG and PhD level.

Supervision experience: 15+ UG, PG and PhD supervision.

Biomedical Science Tutor and University Lecturer (PhD, BSc)

• Doctorate/PhD in Biomedical Sciences, Kings College London
• BSc Physiology, St. George’s, University of London
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• External examiner for over 8 universities and colleges
• Deputy Programme Director for Biomedical Science programmes

Teaching experience: Supervisor, marker and examiner with faculty positions at Kings College London, Middlesex University, University of Salford and University of Sussex.

Years taught : over 25 years of teaching and supervision at UG, PG and PhD level.

Supervision experience: 35+ UG, PG and PhD supervision and ongoing.

Pharmacy Tutor and University Lecturer (PhD, MPharm )

• Doctorate/PhD in Pharmaceutical Sciences, Kings College London
• MPharm, School of Pharmacy, University of London (now part of UCL)
• Over 48 peer-reviewed publications
• Deputy module coordinator for M.Pharm and MSc courses
• External and internal examiner for 10 PG and PhD students

Teaching experience: Examiner, supervisor and faculty positions at University of London, University of Surrey, Nottingham School of Pharmacy, University of Manchester, University of  Hertfordshire.

Years taught : over 18 years of teaching  and supervision at UG and PG levels.

Supervision experience: 28+ UG and PG supervision  and assessment as external and internal examiner.

Engineering Tutor and University Lecturer (PhD, MEng )

• Doctorate/PhD in Mechanical, Aerospace & Aeronautical Engineering, University of Cambridge
• MEng Mechanical Engineering (Distinction), Queen Mary, University of London (Russell group)
• Author of 12+ peer-reviewed journals and articles
• Design engineer and lead researcher with Rolls-Royce and BMW

Teaching experience: Admission tutor, assessor, academic mentor and supervisor for BEng, MEng levels, Queen Mary, University of London, Sheffield Hallam University and School of Mechanical Engineering of NTUA.

Years taught : over 8 years of teaching and supervision at UG and PG level.

Supervision experience: 15+ UG and PG supervision and ongoing.

Architecture & Design Tutor and University Lecturer (PhD ARB/RIBA, MArch , BA )

• Doctorate/PhD in Architecture, Bartlett School of Architecture, UCL
• MArch, University of Bath
• BA (Hons) – ARB/RIBA, Kent School of Architecture and Planning
• Chartered architect and design consultant
• Author of several peer-reviewed journals and articles

Teaching experience: Tutor, marker and examiner for various design and architecture courses at University of Manchester, University of Bath and University of Michigan.

Years taught : over 12 years of teaching  and supervision at UG, PG and PhD level.

Supervision experience: 15+ UG  and PG supervision.

Mathematics Tutor, University Lecturer and Deputy Head of Research (PhD, MASt, BA)

• Doctorate/PhD Pure Mathematics, University of Cambridge
• Part III (MASt), University of Cambridge
• Bachelor’s degree, Mathematics, University of Warwick
• 30+ peer reviewed publications
• Selection committee and marker for the National Mathematical Olympiad

Teaching experience: Deputy Head of Research and faculty positions at University of London, University of Bath and University of St Andrews School of Mathematics & Statistics.

Years taught : over 20 years of teaching  and supervision at UG, PG and PhD level.

Supervision experience: 40+ UG, PG and PhD supervision and ongoing.

Law Tutor, Senior Lecturer and Examiner ( PhD , LLM, LLB)

• Doctorate/PhD in Law, University of Edinburgh
• Masters in Law, LL.M – Harvard Law School
• Bachelor of Law, University of Bologna
• 50+ peer reviewed publications, book chapters , encyclopaedia entries
• Legal advisor for several national and international charities, UNDP and UNHCR

Teaching experience: External examiner and faculty positions at University of London, Oxford University, University of Law, UCL School of Law, University of Exeter, European University Institute.

Years taught : over 25 years of teaching  and supervision at UG, PG and PhD level.

Supervision experience: 30+ UG, PG and PhD supervision and ongoing.

Psychology & Statistics Tutor, University Lecturer & Chartered Psychologist ( CPsychol /MBACP, PhD, BSc)

• Doctorate/PhD in Psychology, University of Reading
• BSc Psychology, University of Reading
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Supervision experience: 25+ UG, PG and PhD supervision and ongoing.

Nursing Tutor and University Lecturer (RN, RNT, NMC, PhD, MSc, BNurs)

• Doctorate/PhD in Adult Nursing, Imperial College London
• MSc Clinical practice, University of Leeds
• BSc in Nursing, Kingston University
• Journal Editorial Board for international peer-reviewed nursing journals –Wiley & sons
• School examinations officer and examiner for UG and PG students
• Clinical supervisor for numerous clinical research facilities at NIHR/Wellcome Trust, Royal free hospital and Leeds Teaching Hospitals NHS Trust

Teaching experience: Lead Nursing supervisor with faculty positions at Imperial College London, Faculty of Medicine for Nurses and allied health professionals, Cardiff University and University of Leeds.

Years taught : over 15 years of teaching  and supervision at UG and PG levels.

Supervision experience: 28+ UG and PG supervision of Nurses and Clinical science students.

Tutor & University Lecturer in Accounting & Finance, ACCA, CIMA, AAT and ATT (PhD, ACCA, MSc, BA)

• Chartered Certified Accountant (ACCA)
• Doctorate/PhD in Accounting and Finance, University of Liverpool (Russell group)
• MSc Accounting and Financial Management, Lancaster University
• BA (Hons) Accounting and Finance, Bournemouth University Business School
• Module lead for Financial management, Accounting and Corporate Governance
• Lead Tutor for ACCA, CIMA, AAT and ATT
• Head of mentoring and academic performance for UG and PG students

Teaching experience: Tutor for professional accounting and finance courses with faculty positions at University of Liverpool, Birmingham City University, BPP University, Kaplan college, London School of Business and Finance and Open University.

Years taught : over 15 years of teaching and supervision at UG, PG and professional levels.

Supervision experience: 18+ UG and PG supervision and mentoring.

Statistics Tutor, Senior Lecturer and Module lead (PhD, MSc, BA)

• Doctorate/PhD in Statistics, University of Warwick
• MSc Applied Statistics, University of Oxford
• BA Economics, Trinity College Dublin
• 45+ peer reviewed publications in leading peer-reviewed journals
• Author of book chapters, talks and keynote speaker for various international conferences.

Teaching experience: Module lead and faculty positions at King’s College London, ETH Zurich, Imperial College London and Trinity College Dublin.

Years taught : over 22 years of teaching and supervision at UG, PG and PhD level.

Tutor & University Lecturer for Medicine & Medical entrance exams– UCAT & BMAT (PhD, MBBS, BSc)

• Doctorate/PhD in Clinical Medicine, Imperial College London, School of Medicine
• MBBS, Imperial College London, School of Medicine
• BSc Hons, Surgery and Anaesthesia, Imperial College School of Medicine
• Author of over 35+ peer-reviewed publications and book chapters
• NIHR Academic fellow in Clinical Medicine and Surgery
• University mentor for aspiring medicine students

Teaching experience:  Academic mentor for UCAT and BMAT students for UCL, Imperial and KCL, School of Medicine. Academic Tutor and project supervisor for UG and PG students.

Years taught : over 10 years of teaching and supervision for Medical entrance exams, MBBS and PhD levels.

Supervision experience: 20+ UG, PG and PhD supervision.

Finance Tutor & Associate Professor/ University Lecturer (PhD, MSc, BSc)

• Doctorate/PhD in Finance, University of Cambridge
• MSc Finance, Imperial College London
• BSc Accounting and Finance, University of Warwick
• Deputy director of the MSc and MRes programmes
• Author of over 45+ peer-reviewed publications, 3 book chapters, 6 working papers
• Referee/Reviewer for several peer-reviewed international journals in Finance

Teaching experience: Examiner and faculty positions at University of Cambridge, Imperial College London, London School of Economics and Henley Business School.

Supervision experience: 40+ UG ,PG and PhD supervision.

Tutor & University Professor of Business and Management (PhD, MBA, BA)

• Doctorate/PhD in Business Administration, Manchester Business School
• MBA (Distinction), University of Edinburgh Business School
• BA Business management, London University
• Editorial board member for over 10 international journals in Business and management sciences
• Published and presented over 150 papers in international journals and conferences
• Advisor to multinational companies, and has worked with more than 40 Group CEO’s and board members over 3 decades

Teaching experience: Associate Dean and faculty positions at leading universities across 4 continents including Imperial College London Business School, Cass Business School – City University London and HEC Paris.

Years taught : over 30 years of teaching and supervision at UG, PG and PhD level.

Supervision experience: 100+ UG, PG and PhD supervision and ongoing.

Florida State University

FSU | Department of Statistics

Department of Statistics

• Graduate Program

PhD Degrees

Doctor of philosophy degrees.

The Department of Statistics at FSU offers a PhD in statistics and a PhD in biostatistics. Course programs and exact degree requirements are determined individually for students through consultation with their supervisory committee. General requirements for the PhD degree are in the FSU Graduate Bulletin. See the FSU Graduate Bulletin for the University's degree requirements, requirements for residence, time limits for the degree, and minimum dissertation hours.

Requirements for All Doctoral Students

Required course for all PhD students.

The course STA5910: Supervised Research, "Faculty Research Presentations," must be taken by all PhD students.

Qualifying Examination

This written examination is offered at the beginning of each spring and fall semester, usually shortly before the start of classes. It is normally taken at the beginning of the spring semester of the second academic year of work in the department. The examination is prepared, administered and graded by the graduate student awards and exams committee. This committee forwards student performance on the examination to the graduate director and department chair to be used in the student’s annual evaluation.

The examination will be graded as passed or failed. Students pursuing the PhD who receive a grade of “failed” may retake the examination at a later time. However, FSU allows the examination to be taken only two times. A second failure on the qualifying exam makes the student ineligible to continue in the doctoral program.

Students intending to take this exam must register for STA 8964 during the semester they take the exam. Students retaking the exam must also register for STA 8964 during the semester they retake the exam.

Students must pass the PhD qualifying exam before they can advance to doctoral candidacy and register for dissertation hours. Students receiving department financial support must pass the exam by January of their third academic year.

The PhD qualifying exam is oriented toward problem solving. The exam consists of a list of questions grouped by topic. The materials covered on the exam for the PhD in Statistics and Biostatistics are taken from the courses listed in Table 10. Copies of past qualifying exams are available.

Careful readers will note that the qualifying exam for Statistics includes material from STA 5106 and not STA 5198, whereas the qualifying exam for Biostatistics covers STA 5198 and not STA 5106. A student passing the qualifying exam in one program only will achieve candidacy in that program. A student successfully completing the questions from both sets of required material will be recognized as having passed the qualifying exams for both Statistics and Biostatistics.

Table 10: Courses covering the material included on the PhD Qualifying Exam.

x Statistics Majors only

y Biostatistics Majors only

Essay Examination

After successful completion of the PhD qualifying examination, the student must begin to consider a suitable topic for a dissertation. As an intermediate step between the qualifying examination and the dissertation, PhD students are required to submit an essay that doubles as a proposal for a dissertation topic.

After consultation with the major professor, the student selects a topic and begins initial investigation of the topic to determine whether a thesis in the area is desired. Following this preliminary investigation, the student writes an essay that should contain

• A literature review of the problem, stating what is known about it to date;
• Some preliminary research results;
• A plan for future research.

Additionally, all PhD students will take an exam based on their essay. This examination is conducted in two parts.

• A 40-50 minute oral presentation of the student's essay open to the entire Department of Statistics.
• An oral examination by the student's supervisory committee. This part of the examination will immediately follow the seminar presentation. It is "closed door" and is conducted orally by the student's supervisory committee to determine success in formulating a research area and ability to do research in that area.

The essay should be written with these goals in mind. A copy of the essay should be sent to the department academic assistant and provided to the supervisory committee members at least three weeks before the essay examination.

Dissertation Defense

The dissertation defense is the last department examination for a PhD candidate. This defense follows the same two-part procedure as the essay examination:

• A 40-50 minute oral presentation of the student's dissertation open to the entire Department of Statistics. All members of the university's graduate faculty are invited to attend the seminar.
• An oral examination. This closed-door part of the thesis defense immediately follows the presentation and is administered by the student's supervisory committee.

Academic courtesy requires that the dissertation be submitted to each member of the supervisory committee and to the department chair at least four weeks prior to the date of the oral examination. Individual committee members may have their own requirements or policies regarding timing and it is the student's responsibility to ensure that each committee member's requirements are met and that each member has an adequate opportunity to read the dissertation. A copy of the dissertation should also be sent to the department academic assistant at least four weeks prior to the defense. Faculty interested in the topic may obtain a copy of the dissertation from the department academic assistant before the defense.

The defense must be completed at least four weeks prior to the date on which the degree is to be conferred. Consult the registrar's office or webpage for deadline dates. Students must enroll in STA 8985 during the term in which they defend their dissertation.

Other Requirements

During the final semester of doctoral work, each PhD candidate must comply with a variety of university administrative requirements prior to obtaining the degree. The university also has specific requirements regarding the format for dissertations and abstracts. These requirements are issued by the Graduate School. Each candidate should become familiar with these requirements well in advance of their final semester's work.

All PhD students must take the department courses required for their degree, either the PhD in Statistics or the PhD in Biostatistics.

PhD students must take at least one course each semester for the first three years of study. Beyond the third year and after the departments required coursework has been completed, additional course work other than dissertation research will be determined by the student with the approval of their major professor and their dissertation committee.

All required coursework (as provided in the table of required courses for the degree being sought) except dissertation hours must be taken for a letter grade.

PhD students must demonstrate active involvement in the scholarly community through interaction with faculty and peers. This requirement may be met through participating in various scholarly activities including enrollment in courses, attendance at colloquium, utilization of the library, utilization of university computational facilities, engaging in collaborative study and research beyond the university campus, and attendance and presentations at professional conferences. Note: It is the students responsibility to document this involvement every year as part of their annual review.

Interdisciplinary Option

Students in either PhD program (Statistics or Biostatistics) may choose to pursue research in an interdisciplinary field of study. A student following the interdisciplinary option (IO) will typically take three graduate courses in an outside area related to the student's research area. No more than one of the three IO courses may be a DIS given by another department in the IO area of specialization.

Graduation Requirements

While engaged in dissertation research, students must register for the number of hours of dissertation (STA6980) determined jointly with their major professor (not less than three semester hours) for at least two of the three semesters of the academic year. Students are required to take a minimum of two semester hours of dissertation every semester until they graduate.

In their final semester, students must apply for degree clearance in the first two weeks of the term. Clearance is contingent upon successful completion of your program of study, as filed with the department. Therefore, the program should at all times accurately reflect the coursework taken. The student will be required to account for any discrepancies.

Students not enrolled in the PhD program who plan to continue working towards a PhD degree after earning a masters must contact the academic program specialist in the department to discuss moving into the PhD program. Students already admitted into the PhD program but who would like to apply for the masters degree must also contact the academic program specialist in the department to have the degree program added to their record.

There are many graduation requirements set by the university. Consult the FSU Graduate Bulletin for a comprehensive list.

Transferring Credits from Another University, Waiving Required Classes

The department follows the University's criteria for allowing transfer credits:

"Transfer of courses not counted toward a previous degree from another regionally accredited graduate school (or comparable international institution) is limited to six semester hours, and transfer of courses not counted toward a previous degree within Florida State University is limited to twelve semester hours, except when the departmental course requirement exceeds the thirty-two hour University-wide minimum requirement. In the latter case, additional transfer credit may be allowed to the extent of the additional required hours."

The complete University criteria may be found on the FSU Graduate Bulletin.

For those wishing to use courses from another university to meet the department's courses requirement, the student must obtain approval of the waiver from the instructor in our department who teaches the required course and the graduate director.

A form for applying for the waiver may be obtained from the Department Office.

PhD Degree in Statistics

Students in the PhD in Statistics degree program tailor their academic programs to be consistent with their individual career objectives. Programs can be designed to prepare graduates for careers in research and/or teaching, for careers emphasizing the application of statistics or for careers requiring the development of new statistical methodology.

Required courses for all students seeking the PhD in Statistics are given in Table 11.

Table 11: Required courses for the PhD in Statistics. All courses are three credit hours.

The department requires a minimum of 36 credit hours of coursework for the PhD in Statistics. All required courses must be taken for a letter grade, but up to 6 credit hours of other coursework can be taken S/U.

Students entering the program with equivalent work (as determined by the faculty) from other institutions will not be required to repeat it. However, in preparing a course program, students should keep in mind that they are required to pass the PhD qualifying examination as one step towards the degree. Students entering the graduate program without any prior graduate work in statistics typically begin course work by studying toward the MS degree in mathematical statistics. Students are responsible for the material normally covered in the core course work of the MS in mathematical statistics degree.

Students are strongly encouraged to register for STA 6468, Advanced Topics in Probability and Statistics, whenever topics to be covered are related to the student’s areas of concentration. The final selection of courses will be determined by the student and major professor and supervisory committee.

Doctor of Philosophy in Biostatistics

The Doctor of Philosophy Degree in Biostatistics prepares students for specialized careers in academia, industry, and government. Program graduates will find themselves sought after by employers in such varied areas as biotechnology, public health, pharmaceuticals, AIDS research, epidemiology, insurance, food sciences, and agribusiness. With an aging US population, the development of new drugs, and advances in the understanding of biological functions at the level of individual genes and proteins, the need for more people trained to design studies and analyze data from these research areas continues to increase.

Required courses for PhD in Biostatistics are presented in Table 12.

Table 12: Required courses for the PhD in Biostatistics. All courses are three credit hours.

The department requires a minimum of 36 credit hours of coursework for the PhD in Biostatistics. All required courses must be taken for a letter grade, but up to 6 credit hours of other coursework can be taken S/U. Flexibility is allowed in selecting the additional coursework for the Biostatistics PhD. The final selection of courses will be determined by the student and major professor and supervisory committee.

Financial Support

The department provides financial support for many of its graduate students. The two main ways in which students are funded are through teaching assistantships and research assistantships.

Types of Support

Teaching assistantships are the most common type of support in the department. These are halftime appointments. Students are paid a salary in return for 20 hours of work each week during the fall and spring semesters. Limited teaching assistantships are available each summer. Teaching assistants may be called upon to perform a combination of the following duties:

• Lecture in lower division statistics courses (STA 1XXX, 2XXX).
• Teach recitation sections of low-level statistics courses.
• Grade homework, projects, and exams for lower and upper level undergraduate and graduate level courses.
• Assist FSU students at the Strozier Library statistics help desk.
• Assist faculty with course-related tasks.
• Assist faculty in the Statistical Consulting Center.

Assignment of graduate students to differing duties is based on department need and when possible, student preference.

There are several university requirements that must be met before a graduate student may teach. These requirements are set forth in the document, "University-wide Standards for Teaching Assistants at Florida State University." This document is maintained by and available from the Office of Graduate Studies. Additionally, a TA must pass the departmental course "Teaching in the Discipline" before teaching.

Research assistantships are supported with funds from research contracts or grants, generally from agencies outside the university, held by department faculty. Students receiving such support assist faculty members with their research programs. Usually a student combines duties under this assistantship with their dissertation work, but the exact duties are established by the faculty member providing support.

In recognition of the differing degrees of responsibility of the above tasks, the amount of stipend provided to a student depends on the duties assigned. There are three levels of stipend in the department. The highest pay is reserved for students lecturing their own courses. The medium level is attained by those who teach recitation sections or work in the Statistical Consulting Center, and the third level is for the remaining students. Research assistant pay is determined by the faculty member supplying the salary.

Other avenues of support include competitive assistantships and fellowships available through the University. More general types of support include loans and grants and are administered through the University's Office of Student Financial Aid. Additionally, opportunities for employment in other university units are often available.

Restrictions on Support

Recipients of federal fellowships or traineeships or university fellowships must abide by the conditions of these awards. International graduate students must observe employment restrictions associated with visas issued. These regulations usually confine employment to appointments supportive of their field of study. Graduate students holding assistantships in the department or other units of the university must obtain permission for additional employment from the director of the project providing the assistantship, the faculty advisor or dissertation director, and the department chair. Any outside employment unrelated to the discipline or deemed to substantially lengthen the time to completion of the degree program may not be approved.

Holders of assistantships are required to register for at least nine hours each semester. Students are advised to consult the FSU Graduate Bulletin for the university policy regarding minimum enrollment requirements for assistantship holders and university residence requirements. Note that students not receiving support must also register for a minimum number of hours each term to meet University requirements.

The department expects all students to apply for the in-state residency tuition classification.

Requirements for Continued Department Support

Students receiving department financial support must complete the following to continue to receive it:

1. Master’s degree students who have not been accepted for continuing to the PhD degree will not receive financial support beyond their second year. 2. To be eligible to receive department financial support as a teaching assistant, PhD students must:

(a) Complete both PIE Day 1 and PIE Day 2 training in the first year. (b) Complete the Teaching-in-the Discipline training workshop in the first year. (c) Pass the PhD written qualifying exam by January of their third academic year. (d) Students whose primary language is not English must take and pass the FSU SPEAK exam with a score at least 50 by the end of the spring semester of their second academic year.

3. Financial support as a TA stops at the end of the fifth academic year.

4. For PhD students who have passed their qualifying exam, their financial support will be terminated if they receive two “Unsatisfactory” grades from their advisor in their dissertation study. Students who do not meet these milestones may continue toward their degree, but with no department financial support. The department chair makes the final decision on matters of continued support.

Tutoring for Payment

The Department receives numerous requests for tutors in statistics. Graduate students in statistics may tutor for payment subject to the following policies and procedures:

Under no circumstances is anyone to tutor, for payment, a student taking a course he or she is teaching or assisting with. For example, a graduate student currently teaching STA2023 may NOT tutor any student currently taking STA2023, even if that student is in another section. The graduate student may tutor, however, a student in STA 2122.

Students may engage in tutoring only insofar that it does not detract from their graduate studies. Students on academic probation are not to tutor. Questions regarding these policies may be addressed to the chair.

Students wishing to tutor are requested to submit the following information to the department secretary: a list of courses they wish to tutor and where or how they can be contacted. The department will maintain a file on tutors giving the above information. When requests are received, the caller will be given the information in the tutor file. The department does not make recommendations.

Please remember that tutoring is suggested as a last resort for students having difficulties in their course work. All graduate student instructors in the department are expected to make sufficient time available for office hours for student help.

Advisors and Committee Formation

The advisor provides academic counsel to the student, advises the student in the preparation of a program of study (see below), and approves the program of study. At no time will a student be without a department advisor. Master's students and students who have not yet been admitted to PhD candidacy will be advised by the graduate director.

Students who have passed the PhD qualifying examination should choose a faculty member to direct their dissertation. This selection of a major professor is a decision based upon mutual research interests of the students and their major professors. The department web-page contains faculty information and indicates research interests. Students should indicate their interests to the faculty member with whom they wish to work. Assuming the faculty member agrees, the student then forms a new supervisory committee to replace the one formed during their first term at FSU. Members of the doctoral supervisory committee are selected in consultation with the major professor subject to certain constraints. In addition to the major professor, the supervisory committee must have at least three other members: two other faculty members from the department and a tenured faculty from outside the department. All committee members must have graduate faculty status. The composition of the committee should reflect the student's research interests and areas of concentration. The composition of the committee is flexible and may be altered at the discretion of the student. Approval of the doctoral supervisory committee by the department chair is required.

The doctoral supervisory committee assumes responsibility for the student's academic advisement. It advises the student in the preparation of a doctoral program of study (see below) and must approve it.

Each year an assessment of the progress of the student is made by the student's advisor. The entire committee conducts the PhD essay examination and the dissertation defense.

Program of Study

A student must have on file with the department an approved program of study at all times. This document represents an agreement between the student and department delineating the course requirements the student must satisfy for a degree. The program of study may be amended at any time with the mutual consent of the student and their advisor. In preparing a program of study, the student must be aware of the degree and residence requirements established by the department and by the university. These forms are available from the department secretary and the department webpage. The forms should be typed and signed by the student's committee members and by the department chair. The original is placed in the student's file in the department office. A copy is made for the major professor who uses it in future course advising. The student is responsible for updating this document annually.

Annual Review

Each year a graduate student progress evaluation is conducted. This is a review of the academic performance of each graduate student. Students are informed whether or not their progress is satisfactory and are expected to remedy any deficiencies noted. The review is used by the department chair in decisions pertaining to the continuation of students in the program. Students not making timely and satisfactory progress toward their intended degree will not be continued in the department. The review is performed by the graduate director or, for students admitted to PhD candidacy, their dissertation director.

The department chair makes the final decision on matters of continuance in the department's degree programs.

The Student Advisory Committee

The Department of Statistics, through the Student Advisory Committee (SAC), participates in the university-wide program which promotes active involvement of students in academic decision making. The SAC consists of one representative each from the first and second year classes, two advanced representatives, and two officers.

The main function of the committee is to act as a liaison between faculty and students. By making themselves available for comments from both groups, the committee promotes effective communications and student awareness of department policies. A member of the SAC attends department faculty meetings. Some past inputs from SAC to the faculty have been to request new courses and invite specific guest speakers to department colloquia.

In addition, the SAC sponsors social/recreational events and enters teams in various intramural programs available on campus.

SAC members are elected each spring term by the graduate students. A representative of the incoming is class chosen at the beginning of the following fall term.

Statistical Consulting Center

As a service to the university, the department operates the Statistical Consulting Center (SCC).

Department members associated with the SCC offer assistance to faculty and students in the university who require statistical help with their research. Occasional assistance is provided to state agencies or to other community members.

Department Colloquia

The department colloquium is a lecture-discussion series on research and applications in topics of interest to members of the department. Colloquia are presented by faculty members, graduate students and visitors to the department.

Attendance at colloquium is expected of all faculty and graduate students in the department. Suggestions for colloquium presentations are always welcomed, and should be passed to the faculty though the SAC.

The department has an annual speaker competition for graduate students, the Anna and Yongyuan Li presentation award. The student who is judged by the faculty of the awards committee to have made the best presentation for the academic year is given the award.

Statistician and Adjunct Professor of Biostatistics Michael S.

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With 15 years of experience, my professional expertise spans the fields of education, mathematics and statistics. The courses I've organized and taught include: Algebra 1, Algebra 2, Precalculus, AP Statistics, and undergraduate and graduate biostatistics and data analysis. I am currently a statistician with a focus on clinical trials and social sciences, and an adjunct professor in biostatistics. I have a BS in Mathematics, MA in Mathematical Education, an MS in Biostatistics, and am a...

With 15 years of experience, my professional expertise spans the fields of education, mathematics and statistics. The courses I've organized and taught include: Algebra 1, Algebra 2, Precalculus, AP Statistics, and undergraduate and graduate biostatistics and data analysis. I am currently a statistician with a focus on clinical trials and social sciences, and an adjunct professor in biostatistics. I have a BS in Mathematics, MA in Mathematical Education, an MS in Biostatistics, and am a credentialed educator of secondary mathematics in Washington state.

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