140.613.79
Data Analysis Workshop I
Location
Internet
Term
Summer Institute
Department
Biostatistics
Credit(s)
2
Academic Year
2026 - 2027
Instruction Method
Online Synchronous (at least one synch session/week)
Start Date
Monday, June 8, 2026
End Date
Friday, June 12, 2026
M, Tu, W, Th, F, 1:30 - 5:00pm
Auditors Allowed
No
Available to Undergraduate
No
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Contact Name
Frequency Schedule
Every Year
Resources
Prerequisite
Experience in using a statistical analysis package; 140.611-612; or equivalent experience
Enrollment Restriction
This course is not restricted.
Intended for students with a broad understanding of biostatistical concepts used in public health sciences who seek to develop additional data analysis skills.
Emphasizes concepts and illustration of concepts applying a variety of analytic techniques to public health datasets in a computer laboratory using Stata statistical software. Learns basic methods of data organization/management and simple methods for data exploration, data editing, and graphical and tabular displays. Includes additional topics: comparison of means and proportions, simple linear regression and correlation.
Learning Objectives
Upon successfully completing this course, students will be able to:
- Create, save and edit Stata datasets, log files, and DO files or R data.frames/tibbles and script/markdown files
- Use Stata .do files or R script/markdown files to create reproducible analyses
- Use Stata or R to: perform exploratory data analysis for continuous, binary, categorical and time-to-event data; perform paired and unpaired t-tests for differences in group means, compute the corresponding confidence intervals, and parse the relevant pieces of the resulting output; perform a chi-squared test and compute confidence intervals for differences in population proportions, relative risks and odds ratios; perform log rank tests and compute confidence intervals for incidence rate ratios; and perform study sample size computations.
- Use artificial intelligence (AI) tools to support code generation
Upon successfully completing this course, students will be able to:
Methods of Assessment
This course is evaluated as follows:
- 60% Lab Assignments and Quizzes
- 40% Final Project
Students must have a computer with Stata installed.