Statistics Lectures - 23: Introduction To ANOVA & One-Way ANOVA

A series of free Statistics Lectures with lessons, examples & solutions in videos.

This is page twenty-three of the series of free video lessons, “Statistics Lectures”. These lectures covers an introduction to ANOVA - analysis of variance, one-way anova, effect size for one-way anova, post-hoc tests for one-way ANOVA.

Statistics - Lecture 70: Introduction to Analysis of Variance (ANOVA)

ANOVA is a statistical method used to compare the means of two or more groups.
Types of ANOVA:

• Repeated-Measures ANOVA - One factor with at least two levels, levels are dependent.
• Factorial ANOVA - Two or more factors (each of which with at least two levels), levels can be either independent, dependent, or both (mixed). Assumptions in ANOVA:
1. Normality of Sampling Distribution of Mass - The distribution of sample means is normally distributed.
2. Independence of Errors - Errors between cases are independent of one another
3. Absence of Outliers - Outlying scores have been removed from the data set.

Statistics - Lecture 71: One-Way ANOVA

One factor with at least two levels, levels are independent.

1. Define Null and Alternative Hypotheses
2. State Alpha
3. Calculate Degrees of Freedom
4. State Decision Rule
5. Calculate Test Statistic
6. State Results
7. State Conclusion

Statistics - Lecture 72: Effect Size For One-Way ANOVA

The most common measure of effect size for a One-Way ANOVA is Eta-squared.

Statistics - Lecture 73: Post-Hoc Tests for One-Way ANOVA

Example:
Researchers want to test a new anti-anxiety medication. They split participants into three conditions (0mg, 50mg, and 100mg), then ask them to rate their anxiety level on a scale of 1-10. Are there any differences between the three conditions using alpha = 0.05?