| Prerequisites |
|
| ST 351 |
INTRODUCTION TO STATISTICAL METHODS |
4 |
| Mathematics to the level of calculus is recommended but not required |
|
| Statistics Core |
|
| ST 516 |
FOUNDATIONS OF DATA ANALYTICS |
4 |
| ST 517 |
DATA ANALYTICS I |
4 |
| ST 518 |
DATA ANALYTICS II |
4 |
| ST 558 |
MULTIVARIATE ANALYTICS |
3 |
| ST 566 |
TIME SERIES ANALYTICS |
3 |
| ST 595 |
CAPSTONE PROJECT |
3 |
| Computer Science Core |
|
| CS 511 |
PROGRAMMING AND DATA STRUCTURES |
4 |
| CS 512 |
DATA SCIENCE TOOLS AND PROGRAMMING |
4 |
| CS 513 |
APPLIED MACHINE LEARNING (Applied Machine Learning [pending approval]) |
4 |
| Electives in Statistics |
|
| Select 12 credits of the following: |
12 |
|
ST 515
|
DESIGN AND ANALYSIS OF PLANNED EXPERIMENTS |
|
|
ST 525
|
APPLIED SURVIVAL ANALYSIS |
|
|
ST 537
|
DATA VISUALIZATION |
|
|
ST 538
|
MODERN STATISTICAL METHODS FOR LARGE AND COMPLEX DATA SETS |
|
|
ST 539
|
SURVEY METHODS |
|
|
ST 591
|
INTRODUCTION TO QUANTITATIVE GENOMICS |
|
|
ST 592
|
STATISTICAL METHODS FOR GENOMICS RESEARCH |
|
| Total Credits |
45 |
