Biostatistics and Health Analytics, M.S.
The Master of Science (MS) in Biostatistics and Health Analytics is designed for students who have strong quantitative abilities and a desire to apply mathematics, statistics, computer programming and data analysis to health-related issues. The program prepares students for professional biostatistical careers and provides a firm academic foundation for subsequent doctoral study in statistical science.
The field of biostatistics is a STEM (Science Technology Engineering and Mathematics) focus area since the field of biostatistics is a mathematically based science. Starting in 2006, the United States launched a program to increase the number of students who receive training in STEM areas. The program will fill the need for graduates with technical abilities to analyze data and draw inferences.
The twenty-first century is the era of Big Data. Every day, we create 2.5 quintillion bytes of data — so much that 90% of the data in the world today has been created in the last two years alone. It is estimated that 30% of this data comes from the health care industry. This proposed program is designed for students who desire a field that combines quantitative reasoning, coding, and scientific skills to solve problems in health and medicine. Importantly, a master’s degree in Biostatistics and Health Analytics will not only prepare students to handle data, but also to apply analytic techniques to answer important research questions related to health and health care.
Curriculum Overview
Students take courses in public health, theory of biostatistics, methods of biostatistics, and computing. Students finish by doing a capstone project under the direction of a faculty member in the Department of Epidemiology and Biostatistics.
Fieldwork and Research Opportunities
Students will have the opportunity to do research as part of their capstone project
Careers
A graduate of the MS in Biostatistics and Health Analytics will be prepared to work as a biostatistician, data scientist, or data analyst.. The number of students in the US who have received master’s degrees in biostatistics has increased by a factor of seven since 2000. “Data scientist,” “biostatistician,” and “statistician” are often rated as some of the top jobs, measured in terms of salary and job satisfaction
Scholarships and Financial Aid
The College for Public Health and Social Justice offers several ways to help finance graduate education. Opportunities include a limited number of merit-based scholarships and graduate research assistantships. Awards are made to applicants with the highest combinations of GPAs and test scores who complete their applications by the priority deadlines.
For more information, visit the student financial services office online at http://finaid.slu.edu.
Accreditation
The College for Public Health and Social Justice is fully accredited by the Council on Education for Public Health (CEPH).
Most recent CEPH Self-Study - August 2017
DESIGN: Students should be able to design experiments or data collection strategies to answer research questions in public health.
DATA AND COMPUTING: Students will use the appropriate software to manage and analyze data.
ANALYSIS: Students will develop statistical models for data and make inferences to answer research questions in public health.
COMMUNICATION: Students will describe the process of data collection, and convey the results of statistical analysis, both orally and in writing.
| Code | Title | Credits |
|---|---|---|
| BST 4100 | Theory of Biostatistics I | 3 |
| BST 5025 | Theory of Biostatistics II | 3 |
| BST 4500 | Statistical Learning | 3 |
| BST 5030 | Statistical Programming and Study Planning: SAS | 3 |
| BST 5100 | Introduction to General Linear Modeling | 3 |
| BST 5200 | Survival Data Analysis | 3 |
| BST 5400 | Applied Data Management | 3 |
| BST 5960 | Capstone in Biostatistics | 3 |
| PUBH 5010 | Mission and Practice of Global Public Health | 3 |
| PUBH 5030 | Methodological Approaches to Understanding Population Health | 3 |
| Electives | ||
| Select two courses from among the following: | 6 | |
| Categorical Data Analysis | ||
| Multilevel and Longitudinal Data Analysis | ||
| Bayesian Statistics | ||
| Sampling Theory and Survey Design in Public Health | ||
| Causal Inference | ||
| Spatial Statistics and Disease Mapping | ||
| Total Credits | 36 | |
Continuation Standards
Students must maintain a cumulative grade point average (GPA) of 3.00 in all graduate/professional courses.
Roadmaps are recommended semester-by-semester plans of study for programs and assume full-time enrollment unless otherwise noted.
Courses and milestones designated as critical (marked with !) must be completed in the semester listed to ensure a timely graduation. Transfer credit may change the roadmap.
This roadmap should not be used in the place of regular academic advising appointments. All students are encouraged to meet with their advisor/mentor each semester. Requirements, course availability and sequencing are subject to change.
| Year One | ||
|---|---|---|
| Fall | Credits | |
| BST 4100 | Theory of Biostatistics I | 3 |
| BST 5030 | Statistical Programming and Study Planning: SAS | 3 |
| BST 5400 | Applied Data Management | 3 |
| Credits | 9 | |
| Spring | ||
| BST 4200 | Theory of Biostatistics II | 3 |
| BST 5030 | Statistical Programming and Study Planning: SAS | 3 |
| BST 5100 | Introduction to General Linear Modeling | 3 |
| Credits | 9 | |
| Year Two | ||
| Fall | ||
| BST 5200 | Survival Data Analysis | 3 |
| PUBH 5010 | Mission and Practice of Global Public Health | 3 |
| BST 5XXX | Biostatistics Elective | 3 |
| Credits | 9 | |
| Spring | ||
| BST 4500 | Statistical Learning | 3 |
| BST 5XXX | Biostatistics Elective | 3 |
| BST 5960 | Capstone in Biostatistics | 3 |
| Credits | 9 | |
| Total Credits | 36 | |