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Gain Applied Statistics Skills to Lead the Decision-Making Process
Apply common statistical techniques, such as regression and analysis, to real-world problems.
Communicate data analysis results orally, in writing, and visually in the context of the problem to nonstatistical audiences.
Use statistical software such as R programming, SAS, Python, and Minitab to conduct data analysis.
Create appropriate graphs and tables to visualize data effectively and present business statistics.
Make decisions that stand up to scrutiny from your supervisor, clients, and customers.
Support your projects with proven methodology, a solid plan, and strong data-driven assessments.
Online Applied Statistics Certificate Courses
Online Applied Statistics Certificate Courses
This 12-credit online program can deepen your knowledge of data science and statistical analysis and provide you with:
- training on SAS and Minitab software packages
- a blend of practical and theoretical data-analysis skills
- the knowledge to handle and interpret data using statistical tools
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)
- 3credits
Descriptive statistics, hypothesis testing, power, estimation, confidence intervals, regression, one- and two-way ANOVA, chi-square tests, diagnostics.
- Prerequisite
one undergraduate course in statistics
- 3credits
Analysis of research data through simple and multiple regression and correlation; polynomial models; indicator variables; step-wise, piece-wise, and logistic regression.
- Prerequisite
6 credits of statistics or STAT 500; matrix algebra
Elective Courses (select 6 credits)
- 3credits
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.
- 3credits
A theoretical treatment of statistical inference, including sufficiency, estimation, testing, regression, analysis of variance, and chi-square tests.
- Prerequisite
STAT 414
- 3credits
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:
- 1credit
Selection and evaluation of statistical computer packages.
- Prerequisite
3 credits in statistics
- and:1credit
Intermediate SAS for data management.
- Prerequisite
STAT 480
- and:1credit
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
- 1credit
Builds an understanding of the basic syntax and structure of the R language for statistical analysis and graphics.
- 1credit
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
- 2credits
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
- 3credits
Design principles; optimality; confounding in split-plot, repeated measures, fractional factorial, response surface, and balanced/partially balanced incomplete block designs.
- Prerequisite
STAT 501
- 3credits
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
- 3credits
Models for frequency arrays; goodness-of-fit tests; two-, three-, and higher-way tables; latent and logistics models.
- Prerequisite
STAT 500, STAT 501, and STAT 502; matrix algebra
- 3credits
Analysis of multivariate data; T-squared tests; partial correlation; discrimination; MANOVA; cluster analysis; regression; growth curves; factor analysis; principal components; canonical correlations.
- Prerequisite
STAT 501 and STAT 502; matrix algebra
- 3credits
Theory and application of sampling from finite populations.
- Prerequisite
calculus, 3 credits in statistics (STAT 500 is recommended)
- 3credits
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
- 3credits
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
- 3credits
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
- 3credits
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.
Start or Advance Your Career
Start or Advance Your Career
You can gain a skill set with this certificate 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.
Career Services to Set You Up for Success
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
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.
Ready to take the next step toward your Penn State graduate certificate?
Costs and Financial Aid
Costs and Financial Aid
Learn about this program's tuition, fees, scholarship opportunities, grants, payment options, and military benefits.
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.
2024–25 Academic Year Rates
| 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
| 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 |
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.
Military Benefits
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:
- visit the Tuition Information site
- click the plus sign to expand the table
- select a semester from the World Campus row
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 Head Start toward a Master’s Degree
A Head Start toward a Master’s Degree
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
The applied statistics master’s degree program is designed to help you develop your data-analytic skills and explore 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.
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 StatisticsWho 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.
Regardless of your professional background, this certificate program can help you improve your data-analytic skills.
Set Your Own Pace
Set Your Own Pace
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.
Our online courses typically follow a 12- to 15-week semester cycle, and there are three semesters per year (spring, summer, and fall). If you plan to take a heavy course load, you should expect your course work to be your primary focus and discuss your schedule with your academic adviser.
To Finish Your Certificate in One Year
- Take 2 courses each semester
To Finish Your Certificate in Two Years
- Take 1 course each semester
Timelines may vary based on course availability.
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
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.
How to Apply to Penn State
How to Apply to Penn State
Apply by December 1 to start January 12
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.
Spring Deadline
Apply by December 1 to start January 12Summer Deadline
Apply by April 15, 2026, to start May 18, 2026
Steps to Apply
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.
Qualified applicants will have successfully completed one undergraduate level course in statistics and have knowledge of matrix and linear algebra.
GPA — 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.
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 alumni, 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 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 Fox Graduate School's "Requirements for Graduate Admission" page. Visit the TOEFL website for testing information. Penn State's institutional code is 2660.
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.
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: "Certificate 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. Complete the application.
Admissions Help
If you have questions about the admissions process, contact an admissions counselor at [email protected].
Contact Us
Contact Us
Have questions or want more information? We're happy to talk.
To learn more about the Graduate Certificate in Applied Statistics, 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 protected]
World Campus Admissions Counselors
Phone: 814-863-5386
[email protected]
Learn from the Best
Learn from the Best
The Graduate Certificate in Applied Statistics is offered in partnership with the Penn State Eberly College of Science. You will learn from the same faculty who teach in residential programs at Penn State campuses, and they are experienced in teaching online.
Faculty
Indrani Basak
- DegreePh.D., Statistics, University of Pittsburgh
- DegreeM.S., Statistics, Indian Statistical Institute, Calcutta
- DegreeM.A., Mathematics, University of Pittsburgh
- DegreeB.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
- DegreePh.D., Statistics, Southern Methodist University
- DegreeM.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
- DegreePh.D., Statistics, Cornell University
- DegreeM.S., Statistics, Cornell University
- DegreeB.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
- DegreeM.S., Biostatistics, University of North Carolina
- DegreeB.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
- DegreePh.D., Statistics, Penn State
- DegreeM.S., Statistics, Penn State
- DegreeB.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
- DegreePh.D., Forest Resources, Penn State
- DegreeM.S., Forest Resources and Operations Research, Penn State
- DegreeB.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
- DegreePh.D., Ecology, Penn State
- DegreeM.S., Ecology, Penn State
Dr. Eric Nord is a plant physiological ecologist and quantitative ecologist with an interest in agricultural ecosystems.
Megan Romer
- DegreePh.D., Statistics, Penn State
- DegreeM.S., Statistics, Penn State
- DegreeB.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
- DegreePh.D., Statistics, Penn State
- DegreeB.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
- DegreePh.D., Statistics, Virginia Tech
- DegreeM.S., Applied Math, Indiana University of Pennsylvania
- DegreeB.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
- DegreePh.D., Psychology in Education, University of Pittsburgh
- DegreeM.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
- DegreePh.D., Statistics, University of Minnesota
- DegreeB.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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