Checking Normality in R with swirl
How to use the "three-prong" approach to check for normality
Listed in Teaching Materials | resource by group Teaching with R in Undergraduate Biology
Version 1.0 - published on 13 Jan 2020 doi:10.25334/PQ79-N018 - cite this
Licensed under CC Attribution-ShareAlike 4.0 International according to these terms
Description
This lesson introduces students to the three-pronged approach for checking normality. During the lesson, students visualize the distribution of a continuous numerical variable in a biological data set using histograms and normal quantile plots, and perform a goodness-of-fit test. By comparing their outputs to a known normally distributed variable, students are able to correctly interpret the results of this three-pronged approach when working with data that deviates from a normal distribution.
Contents
Allen_OneWayAnova_swirl.swc(SWC | 7 KB)
Morgan_Normality_LessonPlan.pdf(PDF | 88 KB)- Morgan_Normality_swirl(VAR/WWW/QUBESHUB/APP/SITE/PUBLICATIONS/01740/01885/X6XBQNNWNZ/MORGAN_NORMALITY_SWIRL-5447 | 6 KB)
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Cite this work
Researchers should cite this work as follows:
- Morgan, B. (. (2020). Checking Normality in R with swirl. Teaching with R in Undergraduate Biology, QUBES Educational Resources. doi:10.25334/PQ79-N018
Tags
Teaching with R in Undergraduate Biology
This publication belongs to the Teaching with R in Undergraduate Biology group.
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