The program requires courses specific to the area of statistics and data science, and the student is required to finish ten 4credit courses and two 1credit capstone seminars for a total of 42 credits. An exit exam or final thesis is not required.
Sample Schedule
Fall Semester of the 1st Year (12 credits) 
Math 501: Probability (4) Math 530: Computational Linear Algebra (4) Math 531: Statistical Modeling with Regression (4) 
Spring Semester of the 1st Year (12 credits) 
Math 502: Statistical Inference (4) Math 532: Generalized Linear & Mixed Models (4) Math 535 or Math 570: Advanced Statistical Learning or Data Mining with Multivariate Analysis (4) * 
Fall Semester of the 2nd Year (9 credits) 
Elective Course #1 (4) Elective Course #2 (4) Math 540: Capstone Seminar I (1) 
Spring Semester of the 2nd Year (9 credits) 
Elective Course #3 (4) Elective Course #4 (4) Math 541: Capstone Seminar II (1) 
* If both Math 535 and Math 570 are completed, one will satisfy the required course requirement while the other will be counted as an elective.
Grade Requirements
In addition to the course requirements (24 credits from 6 core courses, 16 credits from 4 elective courses, and 2 credits from 2 capstone seminars), the student must maintain at least a B average (GPA 3.0) and a minimum grade not lower than B– in these courses. In addition, the student must have a minimum grade not lower than B in the two capstone seminars.
Course Catalog
Core Courses (24 credits) 

Course number 
Title 
Credits 
Semester 
Math 501 
Probability 
4 
1F 
Math 502 
Statistical Inference 
4 
1S 
Math 530 
Computational Linear Algebra 
4 
1F 
Math 531 
Statistical Modeling with Regression 
4 
1F 
Math 532 
Generalized Linear & Mixed Models 
4 
1S 
Math 535 / Math 570 
Advanced Statistical Learning / Data Mining with Multivariate Analysis 
4 
1S 
Elective Courses (16 credits from any 4 courses below) 

Course number 
Title 
Credits 
Semester 
Math 534 
Practical Data Analysis 
4 
2* 
Math 536 
Nonparametric Smoothing and Semiparametric Regression 
4 
2* 
Math 537 
Reliability 
4 
2* 
Math 538 
Sequential Analysis 
4 
2* 
Math 553 
Nonparametric Inference 
4 
2* 
Math 554 
Sampling Theory 
4 
2* 
Math 556 
Design of Experiments 
4 
2* 
Math 557 
Survival Analysis 
4 
2* 
Math 559 
Time Series Analysis 
4 
2* 
Math 573 
Applied Probability and Stochastic Processes 
4 
2* 
Capstone Seminars (2 credits) 

Course number 
Title 
Credits 
Semester 
Math 540 
Capstone 
1 
2F 
Math 541 
Capstone 
1 
2S 
Doctoral Level Courses (may be taken as electives) 

Course number 
Title 
Credits 
Semester 
Math 555 
Linear Models 
4 

Math 558 
Multivariate Statistical Analysis 
4 

Math 571 
Advanced Probability Theory 
4 

Math 572 
Stochastic Processes 
4 

Math 579 
Advanced Statistical Inference 
4 
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