Applied Statistics (MS)
Loyola’s Master of Science in Applied Statistics emphasizes applied statistics and predictive modeling which gives students an advantage in evidence-based fields such as biomedical, environmental, marketing, educational, financial, and contract research (CRO) sectors. Our program can also be completed on a part-time basis and while working full-time.
Curriculum
The Master of Science in Applied Statistics requires 30 credit hours of coursework.
Required Courses
| Code | Title | Hours |
|---|---|---|
| STAT 401 | Introduction to Applied Statistics Using R | 1 |
| STAT 403 | SAS Program & Applied Statistics | 3 |
| STAT 404 | Probability & Statistics I | 3 |
| STAT 405 | Probability & Statistics II | 3 |
| STAT 407 | Statistical Design | 3 |
| STAT 408 | Applied Regression Analysis | 3 |
| STAT 495 | Statistical Consulting Capstone | 2 |
| Select Four (4) Elective Courses | 12 | |
| Stochastic Processes | ||
| Categorical Data Analysis | ||
| Applied Survival Analysis | ||
| Math Modeling & Simulation | ||
| Advanced Statistical Inference | ||
| Topics in Biostatistics | ||
| Introduction to Predictive Analytics | ||
| Longitudinal Data Analysis and Mixed Modeling | ||
| Applied Nonparametric Methods | ||
| Topics in Statistics | ||
| Independent Study Statistics | ||
| Total Hours | 30 | |
Specializations
Our flexible program allows students to focus on their interests by choosing a specialization. Possibilities include:
| Specialization | Description |
|---|---|
| Biostatistics | The Biostatistics specialization covers non- and pre-clinical statistical methods, bioassay, statistical genetics, clinical trials, and bioinformatics. |
| Environmental Statistics | The Environmental Statistics specialization addresses Geographic Information Systems (GIS), spatial statistics, and environmetrics. |
| General Applied Statistics | The specialization in General Applied Statistics includes non-medical applications such as actuarial, commercial, data-mining, industrial, marketing, and national defense. |
| Predictive Analytics/Modeling | The Predictive Modeling specialization focuses on big data analytics and modeling. |
Suggested Sequence of Courses
The below sequence of courses is meant to be used as a suggested path for completing coursework. An individual student’s completion of requirements depends on course offerings in a given term as well as the start term for a major or graduate study. Students should consult their advisor for assistance with course selection.
The below suggestion is for Fall full-time entrants. Adjustments are made for Summer or Spring entrants. Adjustments are also done on a case-by-case basis for part-time students or if discussed with the Graduate Program Director.
| Year 1 | ||
|---|---|---|
| Fall | Hours | |
| STAT 401 | Introduction to Applied Statistics Using R | 1 |
| STAT 403 | SAS Program & Applied Statistics | 3 |
| STAT 404 | Probability & Statistics I | 3 |
| STAT 408 | Applied Regression Analysis | 3 |
| Hours | 10 | |
| Spring | ||
| STAT 405 | Probability & Statistics II | 3 |
| Two 400-level STAT Electives | 6 | |
| Hours | 9 | |
| Summer | ||
| One 400-level STAT Elective 1 | 3 | |
| Hours | 3 | |
| Year 2 | ||
| Fall | ||
| STAT 407 | Statistical Design | 3 |
| STAT 495 | Statistical Consulting Capstone | 2 |
| One 400-level STAT Elective 1 | 3 | |
| Hours | 8 | |
| Total Hours | 30 | |
- 1
If no elective is taken during the Summer term, it is expected that students will take two (2) 400-level STAT courses in Fall term Year 2.
Graduate & Professional Standards and Regulations
Students in graduate and professional programs can find their Academic Policies in Graduate and Professional Academic Standards and Regulations under their school. Any additional University Policies supersede school policies.
Learning Outcomes
Upon completion of our MS program in Applied Statistics, students are expected to have:
- Mastered the art and science of choosing and/or developing the appropriate statistical model(s) for a given dataset-situation, and have mastered the skill of interpreting the chosen model.
- Received sufficient exposure to basic theorems and proofs used in introductory probability and statistical inference.
- Worked with data from application fields such as public/global health, medical, industrial and environmental research.
- Received training to ethically apply statistical training in the real world.
- Obtained hands-on experience and assimilated course material via our 2cr Statistical Consulting capstone/practicum class.
- Sufficiently mastered the course and practicum material to either obtain gainful employment in the field of attend a Ph.D. program