M.S. in Statistics and Data Science
Overview
The Statistics and Data Science program accommodates students desiring an applied background for a career in government and industry as well as students desiring a more theoretical background for further graduate studies.
The Master of Science in Statistics and Data Science degree is available in both a thesis (recommended) and a non-thesis option. For students electing the thesis option, the program requires 24 hours of acceptable course work and 6 hours of credit for the thesis. For students not electing to write a thesis, 36 hours of acceptable coursework, including Statistics 5396, are required. Students must enroll in Statistics 5195 each semester of residence. Comprehensive written exams are required of all students. Students who write a thesis may have a portion of the comprehensive examination waived.
Admissions Requirements
- An official transcript, with the four-year baccalaureate degree posted, from the degree-granting institution and copies of transcripts for all other relevant upper-division and graduate work at accredited U.S. institutions or equivalent work and degrees at foreign institutions.
- Statement of Purpose
- 2 Letters of Recommendation
- Applicants whose degrees are from non-English speaking institutions are required to demonstrate English proficiency. Please consult the Graduate School website for required scores.
Degree Plan
Required Credits: 31-37
Code | Title | Hours |
---|---|---|
MS in Statistics and Data Science (All courses require a grade of C or better) | ||
Required Courses: | ||
MATH 5321 | Principles of Analysis | 3 |
MATH 5322 | Linear Algebra | 3 |
or MATH 5330 | Comp Methods of Linear Algebra | |
STAT 5195 | Graduate Seminar | 1 |
STAT 5380 | Mathematical Statistics I | 3 |
or DS 5380 | Math Found of DS I | |
STAT 5381 | Mathematical Statistics II | 3 |
or DS 5381 | Math Found of DS II | |
STAT 5385 | Applied Regression Models | 3 |
STAT 5388 | Multivariate Data Analysis | 3 |
Select a thesis or non-thesis option: | 12-18 | |
Thesis Option | ||
Thesis 1 | ||
Thesis 2 | ||
Plus 6 more hours from Electives list below. | ||
Non-Thesis Option | ||
Graduate Research | ||
Plus 15 additional hours from Electives list below. | ||
Electives: | ||
Data Visualization | ||
Statistical Programming | ||
Applied Experimental Design | ||
Categorical Data Analysis | ||
Post-Genomic Analysis | ||
Special Topics | ||
Stochastic Processes | ||
Time Series Analysis | ||
Statistical Computing | ||
Intro to Statistical Analysis | ||
Statistical Machine Learning I | ||
Statistical Machine Learn. II | ||
Total Hours | 31-37 |