Master of Science in Statistics
This program will give Â鶹´«Ã½s a combination of knowledge of statistical techniques, experience with using these techniques in applied situations, and understanding of the theoretical principles behind these techniques. Students receive training for professional employment in industry or government, and at the same time obtain sufficient theoretical background to qualify them to teach elementary statistics or to continue into more advanced degree programs. The Â鶹´«Ã½ is encouraged to apply for an internship experience (STAT 7120) where it is expected that Â鶹´«Ã½s will collaborate with professional statisticians in an actual work environment with real problems. A minimum of thirty-two hours is required, and the resulting degree is a Master of Science in Statistics.
Admission Requirements
Admission to the masters program in statistics requires candidates have completed an undergraduate program containing a substantial amount of mathematics, including:
- A complete calculus sequence through multiple integration
- A course in probability
- A course in statistical methods
- A course in linear algebra
A complete undergraduate mathematics major is not required.
Application
General application information for the University, as well as specific requirements for individual programs, are incorporated into the online graduate application system.
More information is provided in the applications FAQ page.
Program Requirements
1. Acquire at least 32 credit hours of approved courses from the following groups
Required courses
- STAT 6500: Statistical Theory I (4 hours)
- STAT 6600: Statistical Theory II (4 hours)
- STAT 6620: Applied Linear Models (3 hours)
- STAT 6640: Applied Mixed Models (3hours)
- STAT 6800: SAS Programming (3 hours)
Elective courses
- STAT 5450: Introduction to Bayesian Data Analysis (3 hours)
- STAT 5610: Applied Multivariate Statistical Methods (3 hours)
- STAT 5630: Sample Survey Methods (3 hours)
- STAT 5660: Nonparametric Statistical Methods (3 hours)
- STAT 5820: Time Series Analysis (3 hours)
- STAT 5850: Applied Data Mining (3 hours)
- STAT 5860: Computer Based Data Analysis (3 hours)
- STAT 5870: Big Data Analysis Using Python (3 hours)
- STAT 6040: Fundamentals of Epidemiology and Clinical Trials (3 hours)
- STAT 6350: Spatial Statistics (3 hours)
- STAT 6450: Applied Bayesian Statistics (3 hours)
- STAT 6460: Large Sample Theory (3 hours)
- STAT 6610: Multivariate Statistical Analysis (3 hours)
- STAT 6630: Linear Models (3 hours)
- STAT 6650: Advanced Statistical Inference (3 hours)
- STAT 6660: Advanced Nonparametric Statistical Methods (3 hours)
- STAT 6670: Introduction to Random Processes (3 hours)
- STAT 6680: Categorical Data Analysis (3 hours)
- STAT 6690: Studies in Probability and Statistics (3 hours)
- STAT 6810: Survival Data Analysis (3 hours)
- STAT 7120: Professional Field Experience (3 hours)
2. Pass the department graduate exams which cover material in:
- STAT 6500: Statistical Theory I (4 hours)
- STAT 6600: Statistical Theory II (4 hours)
- STAT 6620: Applied Linear Models (3 hours)
- STAT 6640: Applied Mixed Models (3 hours)
The DGE is typically given at the end of the first year, on Thursday and Friday of the first week of Summer I. For the exact dates contact . Eligible Â鶹´«Ã½s must register by the end of the spring semester to take this departmental exam.
Internships
Students who have passed the DGE, with prior approval of advisor, may elect to complete an internship during one semester in their second year. Internships usually involve working for a firm under the supervision of a statistician. With advisor's approval, the Â鶹´«Ã½ can earn a maximum of three credit hours to count as an elective course. Students may seek internship Â鶹´«Ã½ independently or in cooperation with statistics faculty members. Occasionally internships have become permanent job Â鶹´«Ã½.
Plan of study
Incoming Â鶹´«Ã½s are expected to meet with the graduate advisor to complete a Plan of Study before the end of their first semester. A tentative plan may be submitted online.
Students that receive funding from the department, are expected to complete their program within two academic years.