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Biostatistics and Health Analytics, M.S.

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.
Required Core Courses
BST 5020Theory of Biostatistics3
BST 5025Theory of Biostatistics II3
BST 5100Introduction to General Linear Modeling3
BST 5400Applied Data Management3
PUBH 5030Methodological Approaches to Understanding Population Health3
BST 5961Master's Project3
Concentrations12
Select one of the following:
Elective3
Total Credits33

Continuation Standards

Students must maintain a cumulative grade point average (GPA) of 3.00 in all graduate/professional courses.

Electives

BST 5220Multilevel and Longitudinal Data Analysis3
BST 5230Bayesian Statistics3
BST 5420Sampling Theory and Survey Design in Public Health3
BST 6100Causal Inference3
GIS 5030Geospatial Data Management3
SOC 5670Spatial Demography – Applied Spatial Statistics3
GIS 5120Geospatial Analytics3

Traditional Biostatistics Concentration

BST 5030Statistical Programming and Study Planning: SAS3
BST 5200Survival Data Analysis3
BST 5210Categorical Data Analysis3
BST 5500Statistical Learning3
Total Credits12

Geospatial Health Data Analytics Concentration

GIS 5010Introduction to Geographic Information Systems3
BST 5600R for Spatial Analysis3
BST 5610Spatial Epidemiology and Disease Mapping3
BST 5450Data Visualization3
Total Credits12

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
FallCredits
BST 5020 Theory of Biostatistics 3
BST 5400 Applied Data Management 3
BST 5450 Data Visualization 3
 Credits9
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
 Credits12
Year Two
Fall
BST 5610 Spatial Epidemiology and Disease Mapping 3
BST 5XXXBiostatistics Elective 3
 Credits6
Spring
GIS 5010 Introduction to Geographic Information Systems 3
BST 5961 Master's Project 3
 Credits6
 Total Credits33

Traditional Biostatistics and Health Analytics Concentration 

Plan of Study Grid
Year One
FallCredits
BST 5020 Theory of Biostatistics 3
BST 5400 Applied Data Management 3
BST 5030 Statistical Programming and Study Planning: SAS 3
 Credits9
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
 Credits9
Year Two
Fall
BST 5200 Survival Data Analysis 3
BST 5210 Categorical Data Analysis 3
BST 5500 Statistical Learning 3
 Credits9
Spring
BST 5961 Master's Project 3
ElectiveBiostatistics Elective chosen in consultation with mentor 3
 Credits6
 Total Credits33

Apply for Admission

For additional admission questions please contact:
Bernie Backer
Director of graduate recruitment and admissions
314-977-8144
bernard.backer@slu.edu