Foundations of ANOVA – Assumptions and Hypotheses for One-Way ANOVA (12-3)

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/folders/1n9aCsq5j4dQ6m_sv62ohDI69aol3rW6Q?usp=sharing 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