Begun over 25 years ago, the Master’s of Science in Applied Statistics is a highly respected program at the Manderson Graduate School of Business.
Students in the Master’s of Science in Applied Statistics program can utilize the Marillyn A. Hewson Data Analytics Lab, taking advantage of cutting-edge technology in a collaborative environment. Students do not need a business degree to earn an MS in Applied Statistics. The Master of Science degree in Applied Statistics is a flexible program, allowing students to structure courses in a manner that complements their career objectives.
Admissions
Candidates for admission to applied statistics are normally expected to have completed courses in mathematics equivalent to three semesters of undergraduate calculus and to have a working knowledge of computer programming and linear or matrix algebra.
In addition to the minimum Graduate School admission requirements, to be considered for regular admission an application must include:
- A resume
- At least two letters of recommendation
- A TOEFL score of at least 79, an IELTS score of at least 6.5, a Duolingo score of at least 110, or a PTE score of at least 59 for non-native English speakers who are required to submit an English Language test score.
Note: A GRE/GMAT score is recommended but not required.
Students who do not meet these requirements, but who excel in other areas, may be considered for "Admission with Permission to Continue"
Accelerated Master's Program (AMP) students must meet the minimum admission requirements as listed in the AMP section of this catalog.
See the Admission Criteria section of this catalog for more information.
Curricular Requirements
The M.S. degree in Applied Statistics requires 30 hours to complete. Students can choose a Non-Specific course of study, or one of two Specialized Concentrations; Analytics or Statistics.
| Required Core Courses: | Hours | |
|---|---|---|
| ST 552 | Applied Regression Analy | 3 |
| ST 553 | Appld Multivariate Analy | 3 |
| ST 554 | Math Statistics I | 3 |
| ST 555 | Math Statistics II | 3 |
| ST 560 | Statistical Methods | 3 |
| Choose the Non-specific course of study or the Analytics or Statistics concentration | ||
| Total Hours | 30 | |
Approved Non-Specific Course of Study Electives
Students who choose the Non-Specific course of study, choose 15 hours of electives from the list below.
| Non-Specific Course of Study Electives | Hours | |
|---|---|---|
| ST 521 | Statistical Data Management | 3 |
| ST 522 | Adv Statistical Data Mgt | 3 |
| ST 531 | Data Mining I | 3 |
| ST 532 | Advanced Data Mining | 3 |
| ST 540 | Stat Prog & Comp with R | 3 |
| ST 545 | Intro Stat Learn & Data Mining | 3 |
| ST 561 | Applied Design Expermnts | 3 |
| ST 547 | Data Vis and Analytics in R | 3 |
| ST 597 | Special Topics ((Statistical Consulting)) | 3 |
| ST 597 | Special Topics ((Stochastic Processes)) | 3 |
| OM 500 | MGT Science & Spreadsheet Mod | 3 |
| Or any other graduate level course with faculty approval. | ||
Statistics Specific Concentration
| Statistics Concentration | Hours | |
|---|---|---|
| Required Course | ||
| ST 561 | Applied Design Expermnts | 3 |
| Approved Electives: choose 4 classes from the list below. | 12 | |
| ST 521 | Statistical Data Management | 3 |
| ST 522 | Adv Statistical Data Mgt | 3 |
| ST 531 | Data Mining I | 3 |
| ST 532 | Advanced Data Mining | 3 |
| ST 540 | Stat Prog & Comp with R | 3 |
| ST 545 | Intro Stat Learn & Data Mining | 3 |
| ST 561 | Applied Design Expermnts | 3 |
| ST 547 | Data Vis and Analytics in R | 3 |
| ST 597 | Special Topics (Statistical Consulting) | 3 |
| ST 597 | Special Topics (Stochastic Processes) | 3 |
| Or other electives with program coordinator approval. | ||
| Required Core Classes | 15 | |
| Total Hours | 30 | |
Analytics Specific Concentration
| Analytics Concentration | Hours | |
|---|---|---|
| Required Courses | ||
| ST 521 | Statistical Data Management | 3 |
| ST 522 | Adv Statistical Data Mgt | 3 |
| ST 531 | Data Mining I | 3 |
| ST 532 | Advanced Data Mining | 3 |
| Approved Electives: choose 1 class from the list below. | 3 | |
| Stat Prog & Comp with R | ||
| Intro Stat Learn & Data Mining | ||
| Applied Design Expermnts | ||
| Special Topics (Statistical Consulting or Stochastic Processes) | ||
| MGT Science & Spreadsheet Mod | ||
| Or other elective courses with faculty approval. | ||
| Required Core Classes | 15 | |
| Total Hours | 30 | |
Transfer Credit
Graduate School information on Transfer Credit.
Accelerated Master's Program
Information on the Accelerated Master's Program.
Comprehensive Exam/Capstone
When most coursework is completed, students must pass a written comprehensive examination. The exam can be waived if the student passes a professional exam from; the Actual P Exam, SAS Predictive Exam, or the ASQ Certified Quality Engineer Exam.
Time Limits for Degree Completion Requirements
Graduate School information on Time Limits.
Academic Misconduct Information
Graduate School information on Academic Misconduct.
Withdrawals and Leave of Absence Information
Graduate School information on Withdrawals and Leave of Absence.
Academic Grievances Information
Graduate School information on Academic Grievances.
Grades and Academic Standing
Graduate School information on Grades and Academic Standing.
Graduate School Deadlines Information
Information on Graduate School Deadlines.
Application for Graduation Information
Information on the Application for Graduation.