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Basic Statistics

Author(s): Emily Weigel1, Alycia Lackey2

1. Georgia Institute of Technology 2. Binghamton University

723 total view(s), 264 download(s)

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.

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

Version 1.0 - published on 27 Jan 2020 doi:10.25334/N0T7-DD80 - cite this Last public release: 1.1


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


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