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Interpreting one-factor ANOVA in R with swirl

Author(s): Jeremy Claisse

Cal Poly Pomona

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Summary:
Interpreting One-Factor Analysis of Variance (ANOVA)

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

Version 1.0 - published on 13 Jan 2020 doi:10.25334/SA4D-PF95 - cite this

Description

In this lesson, students will practice interpreting the results of a one-factor analysis of variance (ANOVA). The students will work through two examples. In working through these examples, students do very basic R coding to interpret the structure of the data frames, specify linear models and produce/interpret ANOVA results tables, and do simple calculations to determine effect sizes (pairwise differences between group means). However, much of the code is given to them directly to re-type or modify, but not much prior coding experience is expected. Associated plots are interpreted. Results outputs and plots from post-hoc multiple comparison tests are produced for them, and they practice interpreting them. Students can also watch a short video on the Multiple Testing Problem. They also practice identifying the appropriate Null and Alternative hypotheses associated with one-factor ANOVA.

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