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Master ofApplied Statistics

Summary Courses Careers Costs and Aid

Gain hands-on experience with the latest innovative software programs and study curriculum designed by experts in the field. This online program can help you develop data analysis skills and explore applied statistics without delving too deeply into the foundations of mathematical statistics.

100% Online

Complete your Penn State course work at your own pace and 100% online.

Apply by July 1 to start August 25

30 Credits$1,027 per credit

Broaden Your Skills with a Master’s in Statistics

  • Develop statistical modeling and data-analysis skills.

  • Master the core areas of applied statistics (DOE, ANOVA, Analysis of Discrete Data, MANOVA, and many more).

  • Expand your skills in advanced statistical procedures, R Statistical Programming Language, Statistical Analysis with Python, and sampling theory and methods.

  • Design principles, analyze variances, and design experiments to solve problems.

  • Use SAS and machine learning for predictive analysis and experimental design to solve problems.

  • Learn statistical consulting and preparation and presentation of reports.

The expert curriculum enables you to use industry-standard software such as Minitab, R, Python, and SAS to improve your data analysis proficiency. You’ll select from courses covering a variety of statistical applications areas, including:

  • data mining
  • predictive analytics
  • biostatistics techniques
  • statistical consulting

Most courses within the applied statistics program are also available as individual courses for those looking to fulfill continuing professional development requirements. Read the instructions for how to register for Penn State World Campus courses to learn how you can enroll in any of the upcoming classes on an individual basis.

Of the 30 credits required to graduate, 24 must be courses from the statistics department, and 21 must be at the 500 level. A minimum grade-point average of 3.0 is also required for graduation.

Required Courses (15 credits)

  • 3
    credits

    Probability spaces, discrete and continuous random variables, transformations, expectations, generating functions, conditional distributions, law of large numbers, central limit theorems.

    • Prerequisite

      Statistics — STAT 500 and STAT 501 strongly recommended. Math — A standard three-course calculus sequence (for example, MATH 140, MATH 141, and MATH 230) and knowledge of matrix algebra and linear algebra (similar to MATH 220). If taken more than a few years ago, students are strongly encouraged to review their calculus knowledge.

  • 3
    credits

    A theoretical treatment of statistical inference, including sufficiency, estimation, testing, regression, analysis of variance, and chi-square tests.

    • Prerequisite

      STAT 414

  • 3
    credits

    Analysis of research data through simple and multiple regression and correlation; polynomial models; indicator variables; step-wise, piece-wise, and logistic regression.

  • 3
    credits

    Design principles; optimality; confounding in split-plot, repeated measures, fractional factorial, response surface, and balanced/partially balanced incomplete block designs.

    • Prerequisite

      STAT 501

  • 2
    credits

    General principles of statistical consulting and statistical consulting experience. Preparation of reports, presentations, and communication aspects of consulting are discussed.

    • Prerequisite

      STAT 502 and (STAT 505 or STAT 508 or STAT 557) and (STAT 503 or STAT 504 or STAT 506 or STAT 510)

  • 1
    credit

    Statistical consulting experience including client meetings, development of recommendation reports, and discussion of consulting solutions.

    • Prerequisite

      STAT 580

Elective Courses (15 credits)

  • 3
    credits

    Tests based on nominal and ordinal data for both related and independent samples. Chi-square tests, correlation.

    • Prerequisite

      STAT 200, STAT 220, STAT 240, STAT 250, STAT 301, or STAT 401

  • 1
    credit

    Selection and evaluation of statistical computer packages.

    • Prerequisite

      3 credits in statistics

  • 1
    credit

    Intermediate SAS for data management.

    • Prerequisite

      STAT 480

  • 1
    credit

    This course covers advanced statistical procedures in SAS, including ANOVA, GIM, CORR, REG, MANOVA, FACTOR, DISCRIM, LOGISTIC, MIXED, GRAPH, EXPORT, and SQL.

    • Prerequisite

      STAT 480 and STAT 481

  • 3
    credits

    Introduction, intermediate, and advanced topics in SAS.

    • Prerequisite

      3 credits in statistics

    • Note

      Credit cannot be received for both STAT 483 and STAT 480/481/482.

  • 1
    credit

    Builds an understanding of the basic syntax and structure of the R language for statistical analysis and graphics.

  • 1
    credit

    Builds an understanding of the basic syntax and structure of the R language for statistical analysis and graphics. R is a popular tool for statistical analysis and research used by a growing number of data analysts inside corporations and academia.

    • Enforced Concurrent at Enrollment

      STAT 484

  • 2
    credits

    Due to the pervasiveness of Python as a statistical analysis tool, there is a demand for statisticians to learn Python to perform descriptive and inferential data analysis. The course will take a case study approach to introduce students to Python. Students will learn to work with complex data using Python and will get hands-on experience on how to use Python to conduct statistical analyses.

    • Enforced Prerequisite at Enrollment

      STAT 300 or STAT 460 or STAT 461 or STAT 462 or STAT 500

  • 3
    credits

    Descriptive statistics, hypothesis testing, power, estimation, confidence intervals, regression, one- and two-way ANOVA, chi-square tests, diagnostics.

    • Prerequisite

      one undergraduate course in statistics

  • 3
    credits

    Design principles; optimality; confounding in split-plot, repeated measures, fractional factorial, response surface, and balanced/partially balanced incomplete block designs.

    • Prerequisite

      STAT 501 and STAT 502

  • 3
    credits

    Models for frequency arrays; goodness-of-fit tests; two-, three-, and higher- way tables; latent and logistic models.

  • 3
    credits

    Analysis of multivariate data; T2-tests; particle correlation; discrimination; MANOVA; cluster analysis; regression; growth curves; factor analysis; principal components; canonical correlations.

    • Prerequisite

      STAT 501, STAT 502

  • 3
    credits

    Theory and application of sampling from finite populations.

    • Prerequisite

      calculus, 3 credits in statistics (STAT 500 is recommended)

  • 3
    credits

    Research and quantitative methods for analysis of epidemiologic observational studies. Non-randomized, intervention studies for human health, and disease treatment.

    • Prerequisite

      3 credits in statistics, STAT 250 or equivalent

  • 3
    credits

    Data mining tools are exploring data with regression, PCA, discriminate analysis, cluster analysis, and classification and regression trees (CART).

    • Prerequisite

      STAT 501 or a similar course that covers analysis of research data through simple and multiple regression and correlation; polynomial models; indicator variables; step-wise, piece-wise, and logistic regression

  • 3
    credits

    The objective of the course is to introduce students to the various design and statistical analysis issues in biomedical research. This is intended as a survey course covering a wide variety of topics in clinical trials, bioequivalence trials, toxicological experiments, and epidemiological studies.

    • Prerequisite

      STAT 500

  • 3
    credits

    Identification of models for empirical data collected over time. Use of models in forecasting.

    • Prerequisite

      STAT 462 or STAT 501 or STAT 511

  • 3
    credits

    Statistical Analysis of High Throughput Biology Experiments.

Course Availability

If you're ready to see when your courses will be offered, visit our public LionPATH course search (opens in new window) to start planning ahead.

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As a statistician with a master's degree and the support of Penn State career resources, you can promote your skill set in data science, business, industry, government, health care, and educational and research organizations.

Job Titles Related to This Degree

The demand for trained statisticians continues to increase as the world becomes more dependent on predictive data and numerical reasoning.

The following roles are often held by people with this type of degree:

  • Data Analyst
  • Statistical Analyst
  • Statistical Reporting Analyst
  • Statistician

Employment Outlook for Occupational Fields Related to This Degree

Estimates of employment growth and total employment are provided by the U.S. Bureau of Labor Statistics and are subject to change. While these occupations are often pursued by graduates with this degree, individual outcomes may vary depending on a variety of factors. Penn State World Campus cannot guarantee employment in a given occupation.

Data Scientists

35.2%
employment growth (10 years)
159,630
total employment

Statisticians

31.6%
employment growth (10 years)
30,780
total employment

Career Services to Set You Up for Success

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From the day you're accepted as a student, you can access resources and tools provided by Penn State World Campus Career Services to further your career. These resources are beneficial whether you're searching for a job or advancing in an established career.

  • Opportunities to connect with employers
  • Career counselor/coach support
  • Occupation and salary information
  • Internships
  • Graduate school resources 

Upcoming Event

Master of Applied Statistics Webinar

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Ready to take the next step toward your Penn State master's degree?

Apply by July 1 to start August 25. How to Apply 

Learn about this program's tuition, fees, scholarship opportunities, grants, payment options, and military benefits.

Graduate Tuition

Graduate tuition is calculated based on the number of credits for which you register. Tuition is due shortly after each semester begins and rates are assessed every semester of enrollment.

2024–25 Academic Year Rates

Tuition Rates for the Fall 2024, Spring 2025, and Summer 2025 Semesters
How many credits do you plan to take per semester?Cost
11 or fewer$1,027 per credit
12 or more$12,325 per semester

2025–26 Academic Year Rates

Tuition Rates for the Fall 2025, Spring 2026, and Summer 2026 Semesters
How many credits do you plan to take per semester?Cost
11 or fewer$1,037 per credit
12 or more$12,448 per semester

Financial Aid and Military Benefits

Some students may qualify for financial aid. Take the time to research financial aid, scholarships, and payment options as you prepare to apply. Federal financial aid may only be used to pay for credits used to satisfy program requirements.

Military service members, veterans, and their spouses or dependents should explore these potential military education benefits and financial aid opportunities, as well.

Additional Cost of Attendance Details

To view the detailed list of cost of attendance elements:

Technical Requirements

Review the technical requirements for this program.

For courses where submitted work or examples involve Minitab or SAS software, students are strongly recommended to have access to a computer running a Windows operating system (as opposed to Mac OS).

A figure walking on a path that includes a certificate part of the way through their progress

Show mastery of specific subjects before your degree is complete. Thanks to shared courses across programs, students can often earn a certificate along with their degree in less time than if they earned them separately.

Certificate Program Related to This Degree

Application criteria for the Master of Applied Statistics degree are more rigorous than for the graduate certificate. Based on your application portfolio, if you are at the borderline of admission into the master's program, preference will be given to applicants who have demonstrated excellent performance in the completion of the certificate program. If you are accepted into the master's program, the credits you earn in the certificate program will be applied to the master's degree.

The following certificate can be earned while completing this degree program:

Strengthen your data analysis and statistics skills while training on the latest industry-standard software programs. This online certificate program blends practical and theoretical data analysis and can give you the tools and knowledge you need to handle and analyze data for your organization.

Learn more

Who Should Apply?

If you want to hone your ability to make data-driven decisions, understand predictive analytics, and apply data science to achieve results in your field — whether in business, education, health care, science, government, or technology — the World Campus Master of Applied Statistics could be right for you.

Prepare For Certificate or Accreditation

Students who successfully complete the online master's program have the option to prepare for the SAS Base Programming Certification Exam or to seek PStat® accreditation through the American Statistical Association as an Accredited Professional Statistician™.

Build Your Professional Network

Your fellow students will have bachelor's degrees in agriculture, biology, business, IT, engineering, mathematics, physical or social sciences, and other related fields. The online courses are interactive and collaborative, allowing you to build strong ties with other working professionals and gain perspectives from other disciplines and industries.

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Whether you are looking to finish your program as quickly as possible or balance your studies with your busy life, Penn State World Campus can help you achieve your education goals. Many students take one or two courses per semester.

This 30-credit master's program can be completed in two to five years, depending on whether you take one or two courses each semester.

Convenient Online Format

This program's convenient online format gives you the flexibility you need to study around your busy schedule. You can skip the lengthy commute without sacrificing the quality of your education and prepare yourself for more rewarding career opportunities without leaving your home.

A Trusted Leader in Online Education

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Penn State has a history of more than 100 years of distance education, and World Campus has been a leader in online learning for more than two decades. Our online learning environment offers the same quality education that our students experience on campus.

Information for Military and Veterans

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Are you a member of the military, a veteran, or a military spouse? Please visit our military website for additional information regarding financial aid, transfer credits, and application instructions.

You can learn more about the application process, prerequisites, and what our courses are like.

What criteria are used for selecting new MAS students?

The MAS admissions committee considers grades — particularly in quantitative courses — along with curriculum vitae, letters of recommendation, and a statement of purpose. The committee will also take your prior working experience into consideration.

International students should refer to the the English Proficiency section on the Graduate School website for language requirements and criteria.

Can I take the online MAS program totally online?

Yes, you can take all courses in the MAS program online. There is no residency requirement for this degree.

What will the online MAS diploma actually say?

Your diploma will state that The Pennsylvania State University grants you the degree of Master of Applied Statistics. Neither the diploma nor the transcript will differentiate the mode (online or otherwise) in which you completed the courses or degree. 

If I have taken some courses at Penn State as a nondegree student, can they be transferred to the MAS program?

A maximum of 15 eligible, nondegree credits can be transferred to a degree program at Penn State. For example, credits taken to fulfill Graduate Certificate in Applied Statistics requirements at Penn State may be transferred to the MAS program if you are granted admission.

Can credits from another institution be transferred to the MAS program?

A maximum of 10 credits from an accredited external institution may be considered for transfer to the MAS program. These credits must have been received within the past five years and should not have been used to fulfill any other degree requirement. The syllabus and grades for these courses will be reviewed by the MAS admissions committee to determine whether credit is eligible to be transferred.

What is the math prerequisite for the MAS program?

The math prerequisite for this program is a standard three-course calculus sequence (for example, MATH 140, MATH 141, MATH 230) and sufficient knowledge of matrix algebra.

Is a thesis required for the MAS degree?

There is no thesis requirement for this professional degree. You will need to complete the capstone MAS project, which is a course requirement for the core course STAT 581.

What is the application process if I have been admitted to another graduate degree program at Penn State?

If you have been admitted to a graduate program at Penn State (for example, you have obtained a master’s degree from Penn State), then instead of filing the application form to the Graduate School at Penn State again, you will need to submit the Resume Study/Change of Graduate Degree or Major form to the Graduate School. In addition, you will need to ask your graduate program to send a copy of your previous application material to the MAS admissions committee. You will also need to submit your statement of purpose, any additional transcripts, and three letters of recommendation.

What is the format of the online courses in this program?

Please visit the Online Learning page on the Department of Statistics website for more information.

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Apply by July 1 to start August 25

Application Instructions

Deadlines and Important Dates

Complete your application and submit all required materials by the appropriate deadline. Your deadline will depend on the semester you plan to start your courses.

  • Fall Deadline

    Apply by July 1 to start August 25

  • Spring Deadline

    Apply by November 1 to start January 12

  • Summer Deadline

    Apply by April 1, 2026, to start May 18, 2026

Steps to Apply

  1. For admission to the J. Jeffrey and Ann Marie Fox Graduate School, an applicant must hold either (1) a baccalaureate degree from a regionally accredited U.S. institution or (2) a tertiary (postsecondary) degree that is deemed comparable to a four-year bachelor's degree from a regionally accredited U.S. institution. This degree must be from an officially recognized degree-granting institution in the country in which it operates.

    Prerequisites — The math prerequisite for this program is a standard three-course calculus sequence (for example, MATH 140, MATH 141, and MATH 230) and knowledge of matrix and linear algebra.

    GPA — A minimum undergraduate GPA of 3.0 overall (on a 4.0 scale) is required.

    Transfer Credit — You may transfer up to 10 graduate credits from another accredited program into the degree program, with approval.

  2. You will need to upload the following items as part of your application:

    Official transcripts from each institution attended, regardless of the number of credits or semesters completed. Transcripts not in English must be accompanied by a certified translation. If you are a Penn State alum, you do not need to request transcripts for credits earned at Penn State but must list Penn State as part of your academic history.

    Test Scores — GRE/GMAT scores are not required.

    English Proficiency — The language of instruction at Penn State is English. With some exceptions, international applicants must take and submit scores for the Test of English as a Foreign Language (TOEFL) or International English Language Testing System (IELTS). Minimum test scores and exceptions are found in the English Proficiency section on the Fox Graduate School's "Requirements for Graduate Admission" page. Visit the TOEFL website for testing information. Penn State's institutional code is 2660.

    References (3) — You will need to initiate the process through the online application by entering names, email addresses, and mailing addresses of three references. Upon submission of your application, an email will be sent to each recommender requesting they complete a brief online recommendation regarding your commitment for success in an online program. Please inform all recommenders they must submit the form in order for your application to be complete.

    Program-Specific Questions/Materials

    Personal Statement — Describe your motivation for undertaking graduate studies in statistics.

  3. To begin the online application, you will need a Penn State account.

    Create a New Penn State Account

    If you have any problems during this process, contact an admissions counselor at [email protected].

    Please note: Former Penn State students may not need to complete the admissions application or create a new Penn State account. Please visit our Returning Students page for instructions.

  4. You can begin your online application at any time. Your progress within the online application system will be saved as you go, allowing you to return at any point as you gather additional information and required materials.

    • Choose Enrollment Type: "Degree Admission"
    • Choose "WORLD CAMPUS" as the campus

    Checking Your Status 
    You can check the status of your application by using the same login information established for the online application form. 

  5. 5. Complete the application.

    Penn State Fox Graduate School Application

Admissions Help

If you have questions about the admissions process, contact an admissions counselor at [email protected].

Customer service representative wearing a headset

Have questions or want more information? We're happy to talk.

To learn more about the Master of Applied Statistics, please visit the departmental website or contact:

World Campus Admissions Counselors
Phone: 814-863-5386
[email protected]

Mosuk Chow, Ph.D.
Research Professor
Director of MAS Program
Department of Statistics, Penn State University
315 Thomas Building
University Park, PA 16802
Phone: 814-863-8128
[email protected]

To help you gain the necessary credentials to progress in this flourishing field, Penn State World Campus has partnered with Penn State's Eberly College of Science to offer this professional Master of Applied Statistics degree with some of the same faculty who teach on campus.

Faculty

  • Indrani  Basak

    • Ph.D., Statistics, University of Pittsburgh 
    • M.S., Statistics, Indian Statistical Institute, Calcutta 
    • M.A., Mathematics, University of Pittsburgh 
    • B.S., Statistics, Indian Statistical Institute, Calcutta 

    Dr. Indrani Basak teaches undergraduate and graduate statistics classes.  Her research interests include robust statistical methods, censoring methods, analytic hierarchy process, and multivariate analysis.

  • Priyangi Bulathsinhala

    • Ph.D., Statistics, Southern Methodist University
    • M.S., Statistics, University of Texas at El Paso 

    Dr. Priyangi Bulathsinhala is an assistant teaching professor in the statistics department. She teaches both online and resident classes. She joined the Penn State statistics department in August 2016. Her research interests include applications in spatial statistics.

  • Mosuk  Chow 

    • Ph.D.,  Statistics, Cornell University 
    • M.S.,  Statistics, Cornell University 
    • B.S., Mathematics, Chinese University of Hong Kong 

    Dr. Mosuk Chow is the MAS program director, and her areas of research interest include biostatistics, statistical decision theory, Bayesian inference, and sampling methods. An important question in statistical decision theory is to characterize the set of all optimal procedures. An admissible procedure is optimal in the weak sense that it cannot be outperformed by another procedure completely in all circumstances. It is thus desirable to find necessary conditions for admissible procedures. Her work in decision theory involves finding such necessary conditions, investigating the admissibility properties of various estimators for problems arising from biology, genetics, and fishery.  

  • Allison Deal

    • M.S., Biostatistics, University of North Carolina
    • B.S., Electrical Engineering and Math, Penn State

    Ms. Allison Deal is a senior biostatistician at the University of North Carolina Lineberger Comprehensive Cancer Center. In her role, she provides statistical expertise for grant and protocol submissions, statistical analyses, and abstract and manuscript preparations. To date, she has co-authored more than 300 peer-reviewed articles, including both observational and interventional clinical research.

  • Prabhani Kuruppumullage Don 

    • Ph.D.,  Statistics, Penn State
    • M.S.,  Statistics, Penn State
    • B.Sc., Statistics (First Class Honors), University of Colombo, Sri Lanka 

    Dr. Prabhani Kuruppumullage Don is an assistant research professor in the Department of Statistics. As the assistant director of online programs, she also oversees all operations of the online programs for the department. Prior to joining the department in 2018, she served as an assistant professor of statistics at the University of Rhode Island and completed her post-doctoral training at the Dana-Farber Cancer Institute/Harvard T.H. Chan School of Public Health. Her research interests include statistical computing, statistical genetics, and latent class models.

  • Bruce Lord

    • Ph.D., Forest Resources, Penn State
    • M.S., Forest Resources and Operations Research, Penn State
    • B.S., Forest Science, Penn State

    Dr. Bruce Lord has more than 30 years of experience as a resource economist specializing in the impacts of natural resources upon rural economies. He has made extensive use of survey research to study the economic impacts of the wood products industry and natural resource–based travel and tourism. His research interests include survey design and analysis, natural resource measurements, and economic forecasting.

  • Eric Nord

    • Ph.D., Ecology, Penn State
    • M.S., Ecology, Penn State

    Dr. Eric Nord is a plant physiological ecologist and quantitative ecologist with an interest in agricultural ecosystems.  

  • Megan  Romer

    • Ph.D., Statistics,  Penn State
    • M.S., Statistics,  Penn State
    • B.S., Mathematics and Applied Mathematical Economics,  SUNY Oswego

    Dr. Megan Romer has been teaching online since 2009 when she earned her doctorate from Penn State's Department of Statistics. She enjoys discussing statistical concepts and problems with students. Before returning to school to finish her doctorate, Dr. Romer worked in clinical trials as a senior research support associate. Her primary area of research is in incomplete data.  

  • Scott Roths

    • Ph.D., Statistics,  Penn State
    • B.S., Mathematics,  Kansas State

    Dr. Scott Roths' primary interest is in teaching statistics, including probability and multivariate methods. He teaches both online and at the University Park campus.

  • Matt Slifko

    • Ph.D., Statistics, Virginia Tech
    • M.S., Applied Math, Indiana University of Pennsylvania
    • B.S., Mathematics, University of Pittsburgh at Johnstown

    Dr. Matt Slifko is an assistant teaching professor in the Department of Statistics. Slifko’s interests include statistics and data science education, statistical collaboration, and undergraduate research. His research deals with clustering and predictive modeling in the presence of anomalous data.

  • Andrew Wiesner

    • Ph.D., Psychology in Education, University of Pittsburgh  
    • M.A., Applied Statistics, University of Pittsburgh 

     Dr. Andrew Wiesner's primary research interests are in sports and educational statistics. He serves on the executive committee for the Penn State Center for the Study of Sports in Society and is a board member for the Penn State All-Sports Museum.  Dr. Wiesner has also presented several faculty workshops on interpreting item statistics to improve exams and the fundamentals of test item–writing.     

  • Lingzhou Xue

    • Ph.D., Statistics, University of Minnesota
    • B.S., Statistics, Peking University

    Dr. Lingzhou Xue is a professor in the Department of Statistics. His research interests focus on high dimensional statistics, statistical and machine learning, nonparametric statistics, large-scale optimization, and statistical modeling in biomedical science, business analytics, environmental science, and social science. Before joining the department in 2014, he was a postdoctoral research associate at Princeton University.

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