applied stat charts

Graduate Certificate in
Applied Statistics

Program summary

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.

Application deadline

Apply by April 15 to start May 13

Credits and costs

12 Credits $1,017 per credit

Lead the Decision-Making Process with Applied Statistics

Because your organization depends on your ability to research, analyze, and interpret data to help reduce risk and achieve success, you need to make decisions that stand up to scrutiny from your supervisor, clients, and customers. Graduate study in applied statistics can help you hone your data-analytic skills so that you can be confident that your projects are backed by proven methodology, a solid plan, and strong data-driven assessments.

To help you meet your career goals, Penn State World Campus has partnered with Penn State's Eberly College of Science to offer an online Graduate Certificate in Applied Statistics. 

Why Applied Statistics Online at Penn State?

As a student in Penn State’s online Graduate Certificate in Applied Statistics program, you can increase your understanding of statistical analysis while you train on industry-standard software packages such as Minitab, R, Python, and SAS. This certificate program can give you a solid background in the fundamentals of statistics that extends beyond a software program's capabilities or features. You can gain a skill set that is useful in fields such as business, education, health, science, government, and technology. You can also acquire skills to apply immediately in your workplace, helping to make you a more valuable problem-solver for your organization.

The 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. The online curriculum is based on the resident program and taught by many of the same faculty. The requirements for both the online and resident applied statistics programs are identical.

Choose the Online Graduate Program in Applied Statistics That Is Right for You

Penn State offers an online master’s degree program and an online Graduate Certificate in Applied Statistics.

Master of Applied Statistics

This master’s degree program is designed to help you develop your data-analytic skills and explores the core areas of applied statistics (DOE, ANOVA, Analysis of Discrete Data, MANOVA, and many more) — without delving too deeply into the foundations of mathematical statistics.

Graduate Certificate in Applied Statistics

Regardless of your professional background, this certificate program can help you improve your data-analytic skills. 

Who Should Apply?

This graduate certificate program is a good choice for you if you want to enrich your data-analysis and analytical abilities and gain a greater knowledge of statistics.

Courses

Penn State's 12-credit online Graduate Certificate in Applied Statistics consists of required and elective courses that can deepen your knowledge of statistical analysis and provide you with:

  • training on SAS and Minitab software packages
  • a blend of practical and theoretical data-analysis skills
  • sophisticated tools and knowledge to handle and analyze data

The graduate certificate allows you to simultaneously gain graduate credit and a highly valued skill set. The applied statistics program is designed as a "stand-alone" certificate or can serve as a "step-up" program into a master's degree — including the Master of Applied Statistics degree.

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.

To earn the Graduate Certificate in Applied Statistics, you will take 6 credits of required courses and choose 6 credits of electives based on your professional goals. At least 6 of the 12 credits must come from courses at the 500 level or above. Please note only 3 credits of statistical programming will count towards your certificate. A minimum 3.0 GPA is required to obtain the certificate.

Required Courses (6 credits)

  • 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

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

Elective Courses (select 6 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

      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.

    • or all of:
      • 1
        credit

        Selection and evaluation of statistical computer packages.

        • Prerequisite

          3 credits in statistics

      • and:
        1
        credit

        Intermediate SAS for data management.

        • Prerequisite

          STAT 480

      • and:
        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

  • 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

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

    • Prerequisite

      STAT 462 or STAT 501

  • 3
    credits

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

    • Prerequisite

      STAT 462 or STAT 501; STAT 502

  • 3
    credits

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

  • 3
    credits

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

  • 3
    credits

    Theory and application of sampling from finite populations.

    • Prerequisite

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

  • 3
    credits

    Develops research and quantitative methods related to the design and analysis of epidemiological (mostly observational) studies. Such studies assess the health and disease status of one or more human populations or identify factors associated with health and disease status. To a lesser degree, the course also covers non-randomized, intervention (experimental) studies that may be designed and analyzed with epidemiological methods.

    • Prerequisite

      STAT 500

  • 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

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.

Costs and Financial Aid

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.

2023–24 Academic Year Rates

Tuition rates for the fall 2023, spring 2024, and summer 2024 semesters.

How many credits do you plan to take per semester? Cost
11 or fewer $1,017 per credit
12 or more $12,203 per semester

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

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

Paying for Your Certificate

Students pursuing a certificate are considered "nondegree," a status that is not eligible for federal student aid, including the Federal Direct Stafford Loan program. A private alternative loan may be an option to consider.

Additionally, Penn State offers many ways to pay for your education, including an installment plan and third-party payments. Penn State World Campus also offers an Employer Reimbursement and Tuition Deferment Plan. Learn more about the options for paying for your education.

Students pursuing a degree and meeting all other eligibility requirements may qualify for financial aid.

How to Apply

Deadlines and Important Dates

Your degree application, including receipt of all transcripts, should be received by the following deadlines to be considered complete.

  • Summer DeadlineApply by April 15 to start May 13
  • Fall DeadlineApply by July 1 to start August 26
  • Spring DeadlineApply by December 1, 2024, to start January 13, 2025

Admissions Help

Our admission counselors are available to discuss with you your educational goals, financial aid options, and application deadlines.

Admission Requirements 

For admission to the 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.

Qualified applicants will have successfully completed one undergraduate level course in statistics and have knowledge of matrix and linear algebra.

What You Need

Applications are submitted electronically and include a nonrefundable application fee. 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. Penn State alumni do not need to request transcripts for credits earned at Penn State, but must list Penn State as part of your academic history. If you are admitted, you will be asked to send an additional official transcript. You will receive instructions at that time.

GPA and Test Scores — A minimum 3.0 GPA on a 4.0 scale, in the final two years of undergraduate studies or in your most recent graduate degree, is strongly preferred. Professional experience will be taken into consideration for admission, and exceptions to the GPA requirement may be made for students with special backgrounds, abilities, and interests. If you seek an exception to the GPA requirement, please indicate the reasons for your request on your application.

GRE/GMAT test 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 Graduate School's "Requirements for Graduate Admission" page. Visit the TOEFL website for testing information. Penn State's institutional code is 2660.

Start Your Application

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.

Begin the graduate school application

  • Choose Enrollment Type:  "Certificate Admission" 
  • Choose "WORLD CAMPUS" as the campus
  • Choose "Applied Statistics" as the certificate

Checking Your Status

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

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).

Ready to Learn More?

Get the resources you need to make informed decisions about your education. Request information on this program and other programs of interest by completing this form.

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Ready to take the next step toward your Penn State graduate certificate?

Apply by April 15 to start May 13. How to Apply

Start or Advance Your Career

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You can use the knowledge gained from this program and the support of Penn State career resources to pursue careers in a variety of fields, depending on your goals.


Career Services to Set You Up for Success

Student having a virtual meeting on a laptop with a career counselor

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 

A Head Start toward a Master’s Degree

A figure standing halfway up a set of stairs leading towards a graduation cap

Not only can this program help create opportunities in your career, it can also give you a solid head start toward a full master’s degree.

Certificate Program Related to This Degree

Some or all credits earned for this certificate can be applied to the following Penn State World Campus degree program:

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.

Learn more about the Master of Applied Statistics  

Contact Us

To learn more about the Graduate Certificate in Applied Statistics, offered in partnership with the Penn State Eberly College of Science, please visit the departmental website or contact:

Prabhani Kuruppumullage Don, Ph.D.
Assistant Research Professor
Assistant Director of Online Programs
Department of Statistics, Penn State University
316A Thomas Building
University Park, PA 16802
Phone: 814-865-1348
Email: [email protected]

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

Faculty

  • Indrani  Basak

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

    • Degree
      Ph.D., Statistics, Southern Methodist University
    • Degree
      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 

    • Degree
      Ph.D.,  Statistics, Cornell University 
    • Degree
      M.S.,  Statistics, Cornell University 
    • Degree
      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.  

  • David Hunter

    • Degree
      Ph.D., Statistics, University of Michigan 
    • Degree
      A.B., Mathematics, Princeton University 

    Dr. David Hunter is a professor in the Department of Statistics, where he also serves as co-director of online programs. He was a high school mathematics teacher prior to earning his doctorate in statistics and joining the Penn State faculty in 1999. At Penn State, he has taught statistics at all levels from introductory to graduate levels, and as department head from 2012 to 2018, he oversaw Penn State's rise to national prominence as a center for expertise in statistics education. His research interests include statistical computing, models for social networks, and statistical clustering.

  • Prabhani Kuruppumullage Don 

    • Degree
      Ph.D.,  Statistics, Penn State
    • Degree
      M.S.,  Statistics, Penn State
    • Degree
      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.

  • Eugene J. Lengerich

    • Degree
      V.M.D., Veterinary Medicine, University of Pennsylvania
    • Degree
      M.S., Agricultural Economics and Operations Research, Penn State

    Dr. Eugene Lengerich is a professor of public health sciences and faculty director of the public health preparedness option. He teaches courses on epidemiology, community preparedness and resilience, and the SARS-CoV-2 vaccine. He also mentors students in independent research. He has led health assessments for medical and public health students in domestic and international settings. Prior to joining Penn State, he conducted outbreak investigations as an Epidemic Intelligence Service officer and preventive medicine resident at the Centers for Disease Control and Prevention. Following his experience at the federal level, he led health investigations for the state of North Carolina. His research interests are in outbreak detection and investigation, community and public preparedness, and preparedness education.

  • Bruce Lord

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

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

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

  • Iain Pardoe

    • Degree
      Ph.D., Statistics, University of Minnesota
    • Degree
      M.Sc., Statistics, University of Minnesota
    • Degree
      BSc., Economics and Statistics, University of Birmingham, UK

    Dr. Iain Pardoe teaches and writes online university statistics and math courses from Nelson, British Columbia, Canada. He teaches at Thompson Rivers University and Statistics.com, as well as at Penn State. His main teaching interest is applied statistics, particularly regression, and he is the author of Applied Regression Modeling (second edition, Wiley, 2012). Dr. Pardoe has broad experience in regression modeling and graphics, Bayesian analysis, and statistical computing. He has also been involved with statistical consulting projects in criminal justice, manufacturing demand, scheduling, and eco-labeling marketing.  

  • Megan  Romer

    • Degree
      Ph.D., Statistics,  Penn State
    • Degree
      M.S., Statistics,  Penn State
    • Degree
      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

    • Degree
      Ph.D., Statistics,  Penn State
    • Degree
      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.

  • Eduardo Santiago

    Degree
    Ph.D., Industrial Engineering and Operations Research, Penn State

    Dr. Eduardo Santiago's research interest is in design of experiments (DOE), specifically the algorithmic creation of optimal designs. He has more than 10 years of industry experience working as a consultant in automotive, food and beverage, pharmaceutical, medical device, insurance, logistics, and chemical industries. Dr. Santiago has written several papers in different areas, including DOE and statistical process control. He has designed and co-developed a control chart available in Minitab to monitor adverse events, such as nosocomial infections and urinary tract infections.  

  • Aleksandra  Slavković

    • Degree
      Ph.D., M.S., Statistics, Carnegie Mellon University 
    • Degree
      Master of Human-Computer Interaction, Carnegie Mellon University 
    • Degree
      B.A., Psychology, Duquesne University 

    Dr. Aleksandra Slavković is co-chair of the Applied Statistics program, and her past and current research interests include usability evaluation methods, human performance in virtual environments, statistical data mining, application of statistics to social sciences, algebraic statistics, and statistical approaches to confidentiality and data disclosure. Her dissertation work focuses on statistical methodologies for disclosure limitation and data confidentiality, and presents new theoretical links between disclosure limitation, statistical theory, and computational algebraic geometry.  

  • Andrew Wiesner

    • Degree
      Ph.D., Psychology in Education, University of Pittsburgh  
    • Degree
      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.     

  • Manel  Wijesinha

    • Degree
      Ph.D., Statistics, University of Florida
    • Degree
      M.S., Statistics, University of Florida 
    • Degree
      B.S., Mathematics, University of Sri Lanka, Colombo 

    Dr. Manel Wijesinha focuses her research primarily on optimal designs in multi-response regression models. She has expanded her research areas to include dose response experiments and microarray data analysis. In these areas of biostatistics, she finds many opportunities to apply her optimal design expertise.  

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Ready to take the next step toward your Penn State graduate certificate?

Apply by April 15 to start May 13. How to Apply