Support

Support Options

  • Knowledge Base

    Find information on common questions and issues.

  • Support Messages

    Check on the status of your correspondences with members of the QUBES team.

Contact Us

About you
About the problem

Basic Statistics

By Emily Weigel1, Alycia Lackey2

1. Georgia Institute of Technology 2. Binghamton University

The students will practice identifying the appropriate basic statistical tests when given a scenario and learn how to run and interpret those statistical tests in R.

Listed in Teaching Materials | resource by group Make Teaching with R in Undergraduate Biology Less Excruciating

Version 1.1 - published on 07 Oct 2020 doi:10.25334/ZGZJ-7N56 - cite this

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

Description

This lesson centers around introducing 4 fundamental statistical tests used in biology: correlations, t-tests, ANOVAs, and X2 (chi-square) tests. Students will first work through a worksheet to identify when each test should be conducted and what the appropriate research hypothesis would be for each experiment. Students then turn to swirl to dig into statistical hypotheses in the context of these scenarios to run and interpret statistical analyses in R.

Learning objectives:

  1. Identify experimental variables and the appropriate basic statistical test for a given scenario
  1. Practice coding elements necessary to run a statistical test in R
  1. Interpret the output of a statistical test relative to a research question/hypothesis

 

Contents

Cite this work

Researchers should cite this work as follows:

Tags

Notes

Correction of a minor typo in the guiding text of the lesson.

Make Teaching with R in Undergraduate Biology Less Excruciating

When watching a resource, you will be notified when a new version is released.