The 21st 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. Saint Louis University's Master of Science in Biostatistics and Health Analytics prepares students to handle this data while applying analytic techniques to answer important research questions related to health and health care.
Program Highlights
This program is designed for SLU students interested in a field that combines quantitative reasoning, coding and scientific skills to solve problems in health and medicine. It is suited for those with strong quantitative abilities and a desire to apply mathematics, statistics, computer programming and data analysis to health-related issues.
An M.S. in biostatistics and health analytics can prepare students for professional biostatistical careers and provides a firm academic foundation for subsequent doctoral study in statistical science.
Biostatistics is a science, technology, engineering and mathematics (STEM) focus area because biostatistics is a mathematically based science. In 2006, the United States launched a program to increase the number of students who receive training in STEM areas. This program will fill the need for graduates with technical abilities to analyze data and draw inferences.
Curriculum Overview
Students take courses in public health, the 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.
Two Concentrations Available
Students interested in learning skills across a broad spectrum of biostatistics and data analytics can choose the traditional biostatistics concentration. Those who want to apply their skills to geospatial data can choose the geospatial health data analytics concentration. Both programs require a core set of material on biostatistics and analytics, and each concentration has its own requirements for completion.
Fieldwork and Research Opportunities
Students will be able to do research as part of their capstone project.
Careers
Graduates of SLU's M.S. in biostatistics and health analytics are prepared to work as biostatisticians, data scientists or data analysts.
Data scientists, biostatisticians and statisticians are often rated as among the nation's top jobs, measured in salary and job satisfaction.
Admission Requirements
Applicants should have a bachelor's degree in a science-related field, such as chemistry, biology, physics, mathematics, engineering, etc., with an overall GPA of 2.5 or higher. At least one semester of calculus and one introductory statistics course are required.
Tuition
Tuition Per Credit
Tuition
Cost Per Credit
Graduate Tuition
$1,400
Additional charges may apply. Other resources are listed below:
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.
Saint Louis University's College for Public Health and Social Justice is fully accredited by the Council on Education for Public Health (CEPH). To see our most recent accreditation documentation, please visit the College for Public Health and Social Justice website.
Learning Outcomes Common to Both Concentrations
Foundations: Students should be able to apply foundational principles of probability and statistics to develop methods for estimation and hypothesis testing.
Analysis: Students will apply advanced statistical methods to analyze data and make inferences to answer research questions in public health.
Communication: Students will describe the process of data collection, the application of statistical methodology, and the results of statistical analysis orally and in writing.
Additional Learning Outcomes for Traditional Biostatistics Concentration
Data and computing: Students will apply the appropriate software to collect, store, manage, clean and analyze data.
Design: Students should be able to design experiments or data collection strategies, including sample size requirements, to answer research questions in public health.
Additional Learning Outcomes for Geospatial and Health Data Analytics Concentration
Data management: Students will acquire, manage, analyze, and display geospatial health data.
Spatial and Spatio-temporal inference: Students will build and analyze models to assess the health of populations across both time and geographic regions.
Course List
Code
Title
Credits
Required Core Courses
BST 5020
Theory of Biostatistics
3
BST 5025
Theory of Biostatistics II
3
BST 5100
Introduction to General Linear Modeling
3
BST 5400
Applied Data Management
3
PUBH 5030
Methodological Approaches to Understanding Population Health
Students must maintain a cumulative grade point average (GPA) of 3.00 in all graduate/professional courses.
Electives
Course List
Code
Title
Credits
BST 5220
Multilevel and Longitudinal Data Analysis
3
BST 5230
Bayesian Statistics
3
BST 5420
Sampling Theory and Survey Design in Public Health
3
BST 6100
Causal Inference
3
GIS 5030
Geospatial Data Management
3
SOC 5670
Spatial Demography – Applied Spatial Statistics
3
GIS 5120
Geospatial Analytics
3
Traditional Biostatistics Concentration
Course List
Code
Title
Credits
BST 5030
Statistical Programming and Study Planning: SAS
3
BST 5200
Survival Data Analysis
3
BST 5210
Categorical Data Analysis
3
BST 5500
Statistical Learning
3
Total Credits
12
Geospatial Health Data Analytics Concentration
Course List
Code
Title
Credits
GIS 5010
Introduction to Geographic Information Systems
3
BST 5600
R for Spatial Analysis
3
BST 5610
Spatial Epidemiology and Disease Mapping
3
BST 5450
Data Visualization
3
Total Credits
12
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.
Geospatial Health Data Analytics Concentration
Plan of Study Grid
Year One
Fall
Credits
BST 5020
Theory of Biostatistics
3
BST 5400
Applied Data Management
3
BST 5450
Data Visualization
3
Credits
9
Spring
BST 5025
Theory of Biostatistics II
3
BST 5100
Introduction to General Linear Modeling
3
BST 5600
R for Spatial Analysis
3
PUBH 5030
Methodological Approaches to Understanding Population Health
3
Credits
12
Year Two
Fall
BST 5610
Spatial Epidemiology and Disease Mapping
3
BST 5XXX
Biostatistics Elective
3
Credits
6
Spring
GIS 5010
Introduction to Geographic Information Systems
3
BST 5961
Master's Project
3
Credits
6
Total Credits
33
Traditional Biostatistics and Health Analytics Concentration
Plan of Study Grid
Year One
Fall
Credits
BST 5020
Theory of Biostatistics
3
BST 5400
Applied Data Management
3
BST 5030
Statistical Programming and Study Planning: SAS
3
Credits
9
Spring
BST 5025
Theory of Biostatistics II
3
BST 5100
Introduction to General Linear Modeling
3
PUBH 5030
Methodological Approaches to Understanding Population Health
3
Credits
9
Year Two
Fall
BST 5200
Survival Data Analysis
3
BST 5210
Categorical Data Analysis
3
BST 5500
Statistical Learning
3
Credits
9
Spring
BST 5961
Master's Project
3
Elective
Biostatistics Elective chosen in consultation with mentor