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Students will complete a minimum of 33 credit hours of coursework, including 21 hours of required program, a minimum of 12 hours of electives, and demonstration of public health foundations.

The demonstration of the public health foundation is achieved either through completion of a previous public health degree (BPH or MPH) or completion of a Canvas Course covering the foundational knowledge. Students are required to demonstrate knowledge of the public health foundations prior to graduation.


Learning Objectives

  • Demonstrate the ability to construct written or oral communication which accurately presents the results and interpretations of a statistical analysis in an easily comprehendible manner to a collaborating health scientist or other vested audience.

  • Develop a statistical analysis plan which implements biostatistical methodology to address a biomedical research question while remaining aware of the limitations of the methodology.

  • Apply concepts from the intersection between biostatistics and epidemiology as it applies to the analysis of data.

  • Develop code for statistical software to wrangle and analyze data sets using appropriate biostatistical methods.

Core Courses

Core Courses

  • CPH 712 Advanced Epidemiology (3 hours)

  • BST 635 Databases and SAS programming (3 hours)

  • BST 675 Simulation Based Inference for Health Data Science (3 hours)

  • BST 681 Linear Regression (3 hours) 

  • BST 682 Generalized Linear Models (3 hours)

  • BST 693 Statistical Practice in Public Health (3 hours)

  • BST 699 Advanced Biostatics Practice (3 hours)

Electives

  • BST 535 Introduction to R programming (3 hours)

  • BST 631 Design and Analysis of Health Surveys (3 hours)

  • BST 636 Analytic Methods for Mining Healthcare Data (3 hours)

  • BST 655 Introduction to Statistical Genetics (3 hours)

  • BST 661 Survival Analysis (3 hours)  

  • BST 662 Applied Longitudinal Data Analysis (3 hours)

  • BST 663 Analysis of Categorical Data (3 hours)

  • BST 664 Design and Analysis of Clinical Trials (3 hours)

  • BST 676 Theory for Biostatistics Methods (3 hours)

  • BST 701 Bayesian Modeling in Biostatistics (3 hours)

  • EPI 717 Introduction to Causal Inference (3 hours)

Sample Schedule 2 Years

Year 1 Fall Year 1 Spring Year 2 Fall Year 2 Spring
BST 675 BST 635 BST 693 BST 699
BST 681 BST 682 Elective Elective
Elective (BST 535 Suggested) CPH 712 Elective  

Sample Schedule 3 Years

Year 1 Fall Year 1 Spring Year 2 Fall Year 2 Spring Year 3 Fall Year 3 Spring
BST 681 BST 635 BST 675 BST 682 BST 693 BST 699
Elective (BST 535) Elective or CPH 712 Elective Elective or CPH 712 Elective