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Binomial test

By Stephen Gosnell

Baruch College, City University of New York & PhD Program in Biology, The Graduate Center of the City University of New York

This lesson focused on introducing students to binomial data analysis and reinforcing concepts of confidence intervals, p-value interpretation, and one- vs two-sided tests.

Listed in Teaching Materials | resource by group Reducing Barriers to Teaching with R in Undergraduate Biology

Version 1.0 - published on 23 Jan 2019 doi:10.25334/Q4WB30 - cite this

Licensed under CC Attribution-ShareAlike 4.0 International according to these terms


Following the lesson, students should be able to
    •    Download and open swirl package
    •    Input new course material into swirl
    •    Conduct out one- and two-sided binomial tests
    •    Interpret p-values
    •    Construct and interpret Agresti-Coull confidence intervals for binomial data

This swirl resource was used following an introduction to binomial tests (slides @ 

I then discussed swirl with students (introductory statistics class who had been been using R for approximately 3 weeks) and had them download and install the package and course (instructions @ After the swirl lesson students completed an assignment focused on the binomial distribution (
). Note the full lesson (slides, assignments) also included a Bayesian perspective and introduction to ggplot2 that were not part of the swirl course. These can be removed if focus is solely on traditional binomial analysis.

Swirl lesson required ~ 25 minutes. Pre-swirl lecture required ~1.5 hr and post-swirl worksheet required ~ 1 hr.  Removing extra (Bayesian and ggplot2) material should reduce lecture time to ~ 1 hr and worksheet time to 25 minutes.


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Reducing Barriers to Teaching with R in Undergraduate Biology

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