School of Public Health


EPI 510 Epidemiologic Data Analysis (3)

Intended for students planning to take EPI 514. Introduces concepts and programming skills necessary to analyze data sets for case-control and cohort studies. Provides students hands-on experience in using epidemiologic data sets for stratified analyses with SAS and Stata. Prerequisite: EPI 511 or EPI 512. Credit/no-credit only. Offered: W.

Winter 2018

Line Number Section ID Credits Days/Times Room/Bldg Instructor
14591A3.0Wednesday, Friday @ 3:00pm - 4:50pm221 (SOCC)Rachel L. Winer
For a complete listing of Epidemiology courses, their elective categories, and when they are typically offered, please see the Epidemiology Course Planning Sheet

Additional Course Details

This course provides a basic introduction to data management and analysis using R and Stata statistical analysis programs in preparation for EPI 514.  Students will develop data management and programming skills, and conduct basic epidemiologic data analyses.  Instruction will include tutorials, guided coding exercises, and assignments.    

Important Info about STATA Software

Students planning to take Epi 510 must have a copy of STATA 15 or STATA 14 installed on their laptops prior to the first day of class. STATA can be purchased through the STATA website. STATA/IC is sufficient for Epi 510 and Epi 514. There are 6-month ($45), 12-month ($89), and perpetual ($198) license options available to choose from. For guidance on installation, please review the online installation guide.

Topics Covered

  • Introduction to R and STATA
  • Data checking and generating new variables
  • Basic descriptive statistics for data sets
  • Reading in data sets from multiple formats
  • Merging data
  • Basic data management
  • Measures of association
  • Assessing confounding and effect modification
  • Stratified data analysis
  • Longitudinal data structure
  • Basic introduction to coding statistical models in R and STATA
  • Introduction to other epidemiologic software (e.g. Epi Info and Open Epi)

Learning Objectives

  • Develop data management skills for epidemiologic research
  • Gain basic programming skills in R and STATA
  • Conduct basic epidemiologic data analyses in R and STATA
  • Gain a basic level of familiarly of advanced programming in STATA
  • Gain a basic level of familiarity with wider analysis techniques in R

Course Format

Lectures, in-class exercises, mentored work sessions, and homework    

How You Will Be Evaluated

Grades are credit/no credit only. Students are evaluated based on completing a series of assignments to a satisfactory level.    

Contact the Instructors

Stata Instructor: Rachel Winer (
SAS Instructor: Chris Delaney (