Launched over 40 years ago, the Master’s of Science in Applied Statistics (MSAPST) is a highly respected program at the Manderson Graduate School of Business. Students enrolled in the MSAPST program are presented with an opportunity to acquire and enhance quantitative competencies essential for excelling in contemporary analytical professions. This program is meticulously structured to offer flexibility, thereby enabling learners to tailor their coursework to align with specific career aspirations. The curriculum encompasses a diverse range of subjects, from the foundational principles of statistics to the practical implementation of statistical and data science techniques in real-world scenarios.
Furthermore, the program presents additional opportunities for experiential learning through the University of Alabama's Institute of Data and Analytics, which oversees the Marillyn A. Hewson Data Analytics Lab. In this state-of-the-art facility, students have access to advanced technological resources and can collaborate with an interdisciplinary cohort of students and faculty on complex data-driven projects. Importantly, the prerequisite for admission to the Master of Science in Applied Statistics program does not mandate a background in business studies.
The MSAPST program offers robust training in statistics fundamentals and professional development to prepare students for the vibrant job market and foster competency and an interest in analytical research. As a STEM-designated program, APST facilities up to three years of Optional Practical Training (OPT) for international students on an F-1 visa.
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:
- Resume
- At least two letters of recommendation
- 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 for admission. A GRE/GMAT score is required for students who, upon admission, may wish to be considered for some limited scholarships, offered on a competitive basis, depending on availability.
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 one or two Specialized Concentrations; Analytics or Statistics Or one Focused Area of Study (FAS): Data Science.
- A Fall term start is recommended to complete the sequential course path of study
| MSAPST 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 |
| |
Statistics Specific Concentration
| Statistics Concentration | Hours |
| ST 561 | Applied Design Expermnts | 3 |
| 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 |
| |
Analytics Concentration
| Analytics Concentration Courses | 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 |
| 12 |
| Stat Prog & Comp with R | |
| Intro Stat Learn & Data Mining | |
| Applied Design Expermnts | |
| Special Topics (Statistical Consulting) | |
| Special Topics (Stochastic Processes) | |
Focused Area of Study (FAS) Data Science
| FAS Required Courses | Hours |
| ST 540 | Stat Prog & Comp with R | 3 |
| ST 545 | Intro Stat Learn & Data Mining | 3 |
| ST 547 | Data Vis and Analytics in R | 3 |
| 9 |
| ST 561 | Applied Design Expermnts | 3 |
| Statistical Data Management | |
| Adv Statistical Data Mgt | |
| Data Mining I | |
| Advanced Data Mining | |
| Special Topics (Statistical Consulting) | |
| Special Topics (Stochastic Processes) | |
| |
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.
