Applied Statistics, MS

Program Description:

The Department of Mathematics and Statistics offers the Master of Science degree in Applied Statistics. The graduate program is designed primarily to prepare graduates for careers in business, industry, or government, but can be tailored to provide a solid foundation for doctoral studies in statistics. The graduate program in Applied Statistics is open to persons with bachelor's degrees in a variety of fields besides mathematics and statistics. The prior mathematical training needed for entrance into the program has been kept to a minimum to accommodate students with undergraduate majors in fields such as biology, business, or one of the social sciences. The department makes provision for part-time degree candidates by offering all required courses in the late afternoon or evening.

Early consultation with the statistics graduate advisor is recommended, since the advisor works closely with the student in every phase of the program.

Admission Requirements:

Applicants for admission are expected to meet the general requirements for admission to graduate study as established by the School of Graduate Studies. Applicants should have completed a calculus sequence that includes multivariable calculus and a course in linear or matrix algebra. Some experience in computer programming and enough background in probability and statistics to begin basic graduate courses in statistics is also required. This normally means one or two prior courses in probability and statistics, depending on content and level. Applicants with insufficient preparation may be admitted on the condition that they complete certain prerequisite work to be specified by the department at the time of admission. Because of course sequencing, it is best to enter the program at the beginning of fall semester.

Program Learning Outcomes:

Formulate real-world problems in statistical language and make appropriate inferences.
Use statistical software to perform reasonable data analysis on given datasets and interpret the results effectively.
Set up experimental designs and collect random samples based on the designs.

For more information visit:

Program Requirements:

The Master of Science degree in Applied Statistics may be earned by satisfying the degree requirements described below. The Applied Statistics program allows students considerable latitude in designing a course of study. This program is primarily intended to prepare students for professional employment in business, industry, or government; however, it can also form a solid foundation for doctoral study.

All master’s degree candidates are required to pass a comprehensive written examination which must be taken at least one semester before the expected date of graduation. The examination is ordinarily offered during fall semester.

In addition to the requirements of the Graduate School, the following departmental requirements must be met to earn a degree in Applied Statistics. Full-time students normally take two years to complete this program.

I. Required Courses: 18 Hours

STT 6610 - Theory of Statistics I Credit Hour(s): 4
STT 6620 - Theory of Statistics II Credit Hour(s): 4
STT 6660 - Statistical Methods I Credit Hour(s): 4
STT 6670 - Statistical Methods II Credit Hour(s): 4
STT 7910 - Statistical Consulting Credit Hour(s): 2 to 3

II. Electives Courses: 12 Hours

Among the elective courses, at least six credit hours must be from STT 7000-level courses.

STT 6110 - Applied Time Series Credit Hour(s): 3
STT 6210 - Sampling Design Credit Hour(s): 3
STT 6240 - Statistical Quality Control and Improvement Credit Hour(s): 3
STT 6260 - Survival Analysis Credit Hour(s): 3
STT 6640 - Machine Learning Credit Hour(s): 3
STT 7020 - Applied Stochastic Processes Credit Hour(s): 3
STT 7140 - Statistical Modeling for Environmental Data Credit Hour(s): 3
STT 7400 - Categorical Data Analysis Credit Hour(s): 3
STT 7440 - Applied Multivariate Analysis Credit Hour(s): 3
STT 7620 - Advanced Topics in Linear Models Credit Hour(s): 3
STT 7670 - Applied Regression Analysis Credit Hour(s): 3

Total: 30 Hours

Biostatistics Track

In addition to meeting the program requirements listed above, students in the Biostatistics Track focus on tools designed to collect, manage and evaluate biostatistical data.

I. Required Courses: 27 Hours

STT 6610 - Theory of Statistics I Credit Hour(s): 4
STT 6620 - Theory of Statistics II Credit Hour(s): 4
STT 6660 - Statistical Methods I Credit Hour(s): 4
STT 6670 - Statistical Methods II Credit Hour(s): 4
STT 6260 - Survival Analysis Credit Hour(s): 3
STT 6310 - Statistical Methods for Clinical Trials Credit Hour(s): 3
STT 7300 - Advanced Topics in Biostatistics Credit Hour(s): 3
STT 7920 - Biostatistical Consulting Credit Hour(s): 2 to 3

II. Electives Courses: 3 Hours

STT 7020 - Applied Stochastic Processes Credit Hour(s): 3
STT 7140 - Statistical Modeling for Environmental Data Credit Hour(s): 3
STT 7400 - Categorical Data Analysis Credit Hour(s): 3
STT 7440 - Applied Multivariate Analysis Credit Hour(s): 3
STT 7620 - Advanced Topics in Linear Models Credit Hour(s): 3
STT 7670 - Applied Regression Analysis Credit Hour(s): 3