The statistics certificate program provides statistical training for graduate students at ASU and working professionals in the Phoenix metropolitan area.
The program draws upon a variety of faculty research and teaching interests from various academic units so programs of study can be tailored to reflect individual needs and goals. This certificate program is part of the shift in the School of Mathematical and Statistical Sciences' statistics curriculum to include data science coursework. In particular, there are several new machine learning classes that are available to certificate students.
Statistics (Graduate Certificate)
Liberal Arts and Sciences, The College of
Plan of Study
The Plan of Study is the required curriculum to complete the program.
Qualifications for Admission
To apply for the certificate program, the applicant must have:
- a bachelor's degree
- an introductory applied statistics course
- one semester of calculus
- some computer literacy with knowledge of either a programming language, or a statistical software program
Certificate of Statistics Requirements
The certificate program requires a minimum of 15 hours of coursework. No more than 40% of coursework towards the requirements of a graduate certificate can be completed prior to admission to the certificate program.
To qualify for the certificate, a student must complete courses in both regression analysis and analysis of variance/experimental design. The remaining nine credits are taken from the set of approved courses listed below. (SoMSS can approve changes to this list).
The certificate program requires no applied project. A maximum of 9 hours from the approved list of certificate courses can be transferred to the MS Statistics degree.
Approved Course Lists
To receive the Certificate in Statistics, complete 5 of the following courses:
Not all courses will be available to all students. Some may have prerequisites that are not part of this program.
Regression Analysis (one of the following is required)
- IEE 578 - Regression Analysis
- ECN 525 - Applied Regression Models
- STP 530 - Applied Regression
Analysis of Variance/Experimental Design (one of the following is required)
- IEE 572 - Design of Engineering Experiments
- ECN 530 - Experimental Design
- STP 531 - Applied Analysis of Variance
Approved Electives (three required)
- IEE 520 - Statistical Learning for Data Mining
- IEE 545 - Simulating Stochastic Systems
- IEE 570 - Advanced Quality Control
- IEE 571 - Quality Management
- IEE 573 - Reliability Engineering
- IEE 575 - Applied Stochastic Operations Research Methods
- IEE 579 - Times Series Analysis and Forecasting
- IEE 582 - Response Surfaces and Process Optimization
- IEE 672 - Advanced Topics in Experimental Design
- IEE 677 - Regression and Linear Models
- IEE 679 - Time Series Analysis and Control
- ECN 527 - Categorical Data Analysis
- ECN 535 - Multivariate Methods
- ECN 540 - Forecasting
- STP 421 - Probability
- STP 425 - Stochastic Processes
- STP 427 - Mathematical Statistics
- STP 501 - Theory of Statistics I
- STP 502 - Theory of Statistics II
- STP 525 - Advanced Probability
- STP 526 - Theory of Statistical Linear Models
- STP 532 - Applied Nonparametric Statistics
- STP 533 - Applied Multivariate Analysis
- STP 534 - Applied Discrete Data Analysis
- STP 535 - Applied Sampling Methodology
Course offerings under IEE 591, ECN 591, STP 591, IEE 598, ECN 598, or STP 598 can be used toward certificate requirements with approval of SoMSS.
Learn more about the Graduate Certificate in Statistics - Six Sigma Black Belt Program.