ANOVA in RStudio Part 1 | Visualization, Normality Assumption, Homogeneity of Variance

In these two installments, I demonstrate how to run an #ANOVA test in #RStudio.

Specifically, in the first video, I will discuss:
1 Data visualization
2 Assumption 1. Normality (of residuals)
3 Assumption 2. Homogeneity of variances: Levene's test; Bartlett's test

In the second video, I cover:
4 Factorial #ANOVA: one-way, two-way, three-way ANOVA
5 Model fit: AIC, BIC, AICwt, and BICwt
6 Effect size: (Partial) eta^2, omega^2, epsilon^2
7 Post-hoc analysis: "hsd", "bonferroni", "lsd", "scheffe", "newmankeuls", "duncan"
8 Visualize post-hoc results with confidence intervals

GitHub link for downloading the dataset and #R Scripts
https://github.com/AriaAvi/Multivariate-Data-Analysis

Videos on getting started with R:
https://www.youtube.com/watch?v=aCUM4r1ONhg&list=PLTjlULGD9bNIkYLqIzneYcc9Gg2VkEzlZ

Videos on how to interpret ANOVA and report the results:
https://www.youtube.com/watch?v=849LZ24FBEA&list=PLTjlULGD9bNLQz_k3LJlla7x7cKVfnu4R