The assumptions for One-Way ANOVA require a scale-level dependent variable and a categorical independent variable, typically with three or more levels. Check for outliers, independence, and normality. The non-parametric alternative is the Kruskal-Wallis One Way ANOVA test. The null hypothesis for ANOVA is that the means are the same.

This video teaches the following concepts and techniques:
Assumptions and Hypotheses for One-Way ANOVA hypothesis testing

Link to a Google Drive folder with all of the files that I use in the videos including ANOVA datasets. As I add new files, they will appear here, as well.
https://drive.google.com/drive/folder...


Table of Contents:

00:17 - Requirements for One-Way ANOVA
02:04 - Assumptions
05:05 - NHST Settings
06:59 - Critical Value for One-Way ANOVA
08:23 - Finding the Critical Value
09:04 - Homogeneity of Variance