Program Details | Applied Statistics Graduate Certificate

The Graduate Certificate Program in Applied Statistics (GCAS) is primarily designed to provide a companion credential for students in other graduate programs (including Mathematics) who have demonstrated expertise in methods and techniques for the quantitative analysis and modeling of data. Graduate programs that share a common interest in the application of statistical methods to the analysis of data and the solutions of problems include: Psychology, Civil and Environmental Engineering, Economics, Electrical and Computer Engineering, Computer Science, Engineering and Technology Management, Environmental Sciences and Resources, Mechanical Engineering, Political Sciences, Sociology, Urban Studies, Systems Science. However, the GCAS program equally serves those who want to pursue just the graduate certificate.

Students develop both a depth of understanding of methods and a breadth of application across disciplines. It is expected that a student who earns this certificate would be capable of performing sophisticated statistical analysis and modeling for problems within his or her particular discipline. They would also be expected to be able to access and understand consultation with professional statisticians and provide consultation in the application of statistical methods for research purposes and in the solution of practical problems. The goal of the GCAS program is a coordinated plan for which students will be assured of exposure to statistical techniques needed in most applications.

Students are encouraged to meet with their advisor at the beginning of their program and consult with them regularly throughout their program. Please contact the GCAS program adviser during the term prior to the term of anticipated graduation to confirm that all program requirements have been completed.

Core Requirements

This Graduate Certificate credential may be completed with a minimum of 24 credit hours of statistical graduate coursework with no comprehensive exam, while the MS in Statistics requires more extensive coursework and examinations.

Graduate certificate students must have a minimum 3.00 GPA on all courses applied to the program of study, as well as a minimum 3.00 GPA in all graduate-level courses taken at PSU.  Although grades of C+, C, and C- are below the graduate standard, they may be counted as credit toward a graduate certificate with the specific written approval of the program.

The program of study leading to a GCAS requires the successful completion of a minimum of 24 graduate credit hours of coursework distributed as three components:

Applied statistics core sequence: The goal of this sequence is to introduce students to fundamentals of applied statistics. The three-term core course sequence: 

  • Stat 564 Applied Regression Analysis (3 credits) and 
  • Stat 565, 566 Experimental Design: Theory and Methods I, II 

Additional applied statistics courses: The objective is developing a breadth of knowledge in the application of statistical methods within the discipline and in related areas. A minimum of 12 additional hours chosen from the list of interdisciplinary courses below. Please note that 510/610 courses and Stat 551, Stat 552 are not acceptable toward the certificate.

Statistical consulting: To provide experience in dealing with real statistical problems Stat 570 Statistical Consulting (3 credits). Please note that this course is only offered during spring term.

All courses applied to the certificate program must have a B- or better grade. To continue in the program, students are required to maintain regular graduate student status, requiring a cumulative 3.00 GPA for all coursework and a term GPA of at least 2.67.

Theory Courses

  • Mth 667 Stochastic Processes and Probability Theory I
  • Mth 668 Stochastic Processes and Probability Theory II
  • Mth 669 Stochastic Processes and Probability Theory III
  • Stat 561 Mathematical Statistics I
  • Stat 562 Mathematical Statistics II
  • Stat 563 Mathematical Statistics III
  • Stat 661 Advanced Mathematical Statistics I
  • Stat 662 Advanced Mathematical Statistics II
  • Stat 663 Advanced Mathematical Statistics III
  • Stat 664 Theory of Linear Models I
  • Stat 665 Theory of Linear Models II
  • Stat 666 Theory of Linear Models III
  • Stat 671 Statistical Learning I
  • Stat 672 Statistical Learning II
  • Stat 673 Statistical Learning III

Applied Statistics Interdisciplinary Courses

  • CE 566/ESM 566 Environmental Data Analysis
  • CS 545 Machine Learning
  • Ec 572 Time Series Analysis and Forecasts
  • Ec 575 Applied Advanced Econometrics
  • ME 588 Design of Industrial Experiments
  • PA 551 Analytic Methods in Public Administration I
  • PA 552 Analytic Methods in Public Administration II
  • Psy 523 Structural Equation Modeling
  • Psy 524 Research Design in Applied Psychology
  • Soc 593 Quantitative Methods
  • Soc 597 Applied Survey Research
  • Stat 567 Applied Probability I
  • Stat 568 Applied Probability II
  • Stat 571 Applied Multivariate Statistical Analysis
  • Stat 572 Bayesian Statistics
  • Stat 573 Computer Intensive Methods in Statistics
  • Stat 576 Sampling Theory and Methods
  • Stat 577 Categorical Data Analysis
  • Stat 578 Survival Analysis
  • Stat 580 Nonparametric Methods
  • USP 532 Data Collection