Students may transfer into the degree program up to nine credits of course work from another similar graduate degree program, provided that the student earned a grade of B or better in the course and the course content is equivalent to the course taught in the degree program and approved by the program advisor. The university policy provided by the Office of Research and Graduate Studies supersedes the program policy, if any conflict occurs.
Program Requirements
Required Prerequisite Courses (0-6 hours)
| STA 580 | Applied Statistical Methods I | 3(3-0) |
| STA 584 | Mathematical Statistics I | 3(3-0) |
Note: Students who have not taken courses similar to STA 580 and/or STA 584 with comparable contents and textbooks are required to take the pre-requisite courses.
Required Courses I (15 hours)
| STA 575 | Statistical Programming for Data Management and Analysis | 3(3-0) |
| STA 591 | Data Mining Techniques I | 3(3-0) |
| STA 675 | Advanced Statistical Data Management and Simulation | 3(3-0) |
| STA 686 | Multivariate Analysis | 3(3-0) |
| STA 695 | Practicum/Internship | 3(Spec) |
Note: With the approval of the program advisor, students who have taken courses similar to STA 575 and/or STA 591 with comparable contents and textbooks may be allowed to replace the course(s) with elective course(s).
Required Courses II (3 hours)
Select one of the following:
| STA 585 | Mathematical Statistics II | 3(3-0) |
| STA 684 | Theory of Statistical Inference | 3(3-0) |
Required Courses III (9 hours)
Select one of the following tracks:
Track 1: Applied Statistics
| STA 582 | Experimental Designs | 3(3-0) |
| STA 590 | Applied Statistical Methods II | 3(3-0) |
| STA 678 | Categorical Data and Survival Analysis | 3(3-0) |
Track 2: Analytics
| ITC 510 | Software and Data Modeling | 3(3-0) |
| ITC 686 | Big Data Analytics | 3(3-0) |
| STA 691 | Advanced Data Mining Techniques | 3(3-0) |
Electives (3 hours)
Select from the following:
| GEO 501 | Principles and Applications of Geographic Information System | 3(2-2) |
| MTH 586 | Operations Research I | 3(3-0) |
| STA 583 | Nonparametric Statistics | 3(3-0) |
| STA 587 | Statistical Theory and Methods for Quality Improvement | 3(3-0) |
| STA 588 | Sampling Techniques | 3(3-0) |
| STA 589 | Time Series Forecasting | 3(3-0) |
| STA 592 | Six Sigma: Foundations and Techniques for Green Belts | 3(3-0) |
| STA 595 | Introduction to Bayesian Statistics | 3(3-0) |
| STA 682 | Linear Models | 3(3-0) |
| STA 696 | Special Topics in Statistics | 1-6(Spec) |
| STA 697 | Independent Study | 1-9(Spec) |
Note 1: Graduate level courses in any discipline different from Mathematics or Statistics with approval of the program advisor may be used as elective courses.
Note 2: Students who are exempted from STA 575 and/or STA 591 under Required Courses I will take a total of 6 or 9 hours under electives.
Total: 30-36 semester hours
Accelerated M.S. in Applied Statistics and Analytics
Advanced undergraduate students majoring in Mathematics, Actuarial Science and Statistics may want to consider the option by which they can obtain Bachelor of Arts in Mathematics, Bachelor of Science in Actuarial Science or Bachelor of Science in Statistics and their Master of Science in Applied Statistics and Analytics in five years. The accelerated program requirements are stated in the Admission Requirements section below. It allows students to apply 12 credit hours of graduate coursework toward both Bachelor degree and the Master of Science degree.
Admission Requirements, Retention & Termination Standards
To be eligible for the accelerated program, a student must
- Have completed a minimum of 15 credit hours of mathematics, including Calculus III and Linear Algebra with at least a B in each of the mathematics courses taken.
- Have completed at least 9 credit hours of statistics including STA 580 (or equivalent) and STA 584 (or equivalent) with at least a B+ in each of the statistics courses taken.
- Have a grade point average of 3.0 overall, a 3.0 in mathematics and a 3.3 in statistics are required.
- Have completed at least 97 credit hours of undergraduate coursework, including all competency requirement and all but 9 credit hours of University Program requirements.
Degree Requirements
The Accelerated Master of Science in Applied Statistics and Analytics is a 30 hours program (27 hours of coursework and 3 hours of Practicum/Internship).
- Prior to the fourth year, students will complete the pre-requisite courses STA 580 and STA 584.
- There are two tracks in the M.S. program, one in Applied Statistics and the other in Analytics. During the fourth year, students must select one track.
- Students in the Applied Statistics track must complete STA 582, STA 591, STA 675, and STA 585, which will be counted toward both the undergraduate and graduate degrees.
- Students in the Analytics track must complete ITC 510, STA 591, STA 675, and STA 585, which will be counted toward both the undergraduate and graduate degrees.
- Students will complete the Bachelor of Arts or Bachelor of Science degree requirements by the end of the summer term of the fourth year.
- Students will complete the coursework and the Practicum/Internship for the Masters of Science degree requirements by the end of the summer term of their fifth year.
A sample curriculum for a student who has completed 97 credit hours of undergraduate coursework is given below:
Year 4 - Fall (15 hours)
Applied Statistics Track: Undergraduate courses (9 hours), in addition to STA 582 (3 hours) and STA 591 (3 hours).
Analytics Track: Undergraduate courses (9 hours), in addition to ITC 510 (3 hours) and STA 591 (3 hours).
| ITC 510 | Software and Data Modeling | 3(3-0) |
| STA 582 | Experimental Designs | 3(3-0) |
| STA 591 | Data Mining Techniques I | 3(3-0) |
Year 4 - Spring (15 hours)
Both Applied Statistics and Analytics Tracks: Undergraduate courses (6 hours), in addition to STA 675 (3 hours) and STA 585 (3 hours), and an elective for graduate requirement (3 hours).
| STA 585 | Mathematical Statistics II | 3(3-0) |
| STA 675 | Advanced Statistical Data Management and Simulation | 3(3-0) |
Year 5 - Fall (6 hours)
Both Applied Statistics and Analytics Tracks: Courses must include STA 686 (3 hours) and an elective (3 hours).
Year 5 - Spring (6 hours)
Applied Statistics Track: Courses must include STA 678 (3 hours) and an elective (3 hours).
Analytics Track: Courses must include ITC 686 (3 hours) and STA 691 (3 hours).
| STA 678 | Categorical Data and Survival Analysis | 3(3-0) |
| STA 691 | Advanced Data Mining Techniques | 3(3-0) |
| ITC 686 | Big Data Analytics | 3(3-0) |
Year 5 - Summer (3 hours)
Both Applied Statistics and Analytics Tracks: STA 695 (3 hours)