Understanding ANOVA Concepts

Define ANOVA as a statistical tool for comparing means of multiple groups.

Distinguish between different types of ANOVA (One-Way, Two-Way/Factorial, Repeated Measures).

Identify and check the key assumptions needed for ANOVA (independence, normality, homogeneity of variances).

Interpret the components of an ANOVA table (Sources of Variation, Sum of Squares, Degrees of Freedom, F-statistic).

Understand why and how to perform post-hoc tests after a significant ANOVA result.

Apply ANOVA methods to analyze biological data, particularly using SPSS (or similar software like Jamovi).

Interpret software output for ANOVA to determine if significant differences exist between groups.

What if you have THREE or MORE groups?

What is Statistical Power?

What is Effect Size?