Graduate: MS Program
M.S. in Applied Statistics Program
The Department of Mathematics and Statistics offers an M.S. in Applied Statistics degree
program either on campus or completely online. This program requires 30 credit hours of course work at 600 – level or above. It is designed to provide students with excellent data analytics training and problem solving skills for employment in various settings such as health and insurance sectors, government agencies, and business entities.
Upon completing this degree, students will meet the following student learning outcomes (SLOs)
- SLO 1. Basic Understanding: Students demonstrate mastery of fundamental statistical methods.
- SLO 2. Synthesis and In-Depth Understanding with Applications: Students demonstrate the ability to apply statistical methods and appropriate statistical software tools to manipulate and analyze complex data sets.
- SLO 3. Communication Effectiveness: Students demonstrate the ability to communicate findings and results effectively, both orally and in writing.
Degree requirements (30 credit hours):
Core Courses (15 credits) | ||
STA 631 | Introduction to Probability | 3 |
STA 632 | Intro to Mathematical Statistics | 3 |
STA 640 | SAS System Statistical Analysis | 1 |
STA 602 | Statistical Methods for Data Analytics | 3 |
STA 606 | Problem Solving for Data Analytics | 3 |
STA 668 | Consulting Experience | 2 |
Statistics Electives (6-12 credits) | ||
Select at least two more courses from the following: | 6 – 12 | |
STA 622 | Complex Data Analysis | |
STA 635 | Theory of Linear Regression | |
STA 642 | Statistical Computing | |
STA 645 | Nonparametric Statistics | |
STA 655 | Applied Probability Models | |
STA 665 | Analysis of Survival Data | |
STA 670 | Categorical Data Analysis | |
STA 671 | Multivariate Analysis | |
STA 673 | Statistical Linear Models I | |
STA 674 | Statistical Linear Models II | |
STA 675 | Advanced Experimental Design | |
STA 676 | Sample Survey Methods | |
STA 682 | Theory of Time Series | |
STA 703 | Topics in High Dimensional Data Analysis | |
STA 709 | Topics in Computational Statistics | |
Interdisciplinary Electives (0-6 credits) | ||
Select 0-6 credits (with advisor’s approval) through any STA courses at the 600-level or above or from mathematics, computer science, economics, information system & supply chain management, education research methodology, informatics and analytics etc. | 0-6 | |
Project (Capstone Experience) (3 credits) | ||
Each student must complete a capstone project. | 3 |