Anova

Each observation must be independent of the others. Interpreting the Results When you run an ANOVA, you’re looking for the p-value .

If you have four groups, you’d need to run six separate t-tests to compare them all. Every time you run a test, there's a 5% chance of a "false positive" (Type I error). By the time you finish those six tests, your chance of making an error has skyrocketed. ANOVA solves this by doing it all in one "omnibus" test, keeping your error rate in check. How ANOVA Works (The Simple Version) ANOVA looks at two types of variation: Each observation must be independent of the others

Example: Comparing weight loss based on both and exercise intensity . 3. MANOVA (Multivariate ANOVA) Every time you run a test, there's a

The simplest form. Use this when you have with three or more levels. How ANOVA Works (The Simple Version) ANOVA looks

Understanding ANOVA: The Powerhouse of Statistical Comparison

The "spread" (variance) should be roughly equal across all groups.