# Statistics Lectures - 24 (ANOVA)

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

These lectures continue the discussion on ANOVA - analysis of variance.

This is page twenty-four of the series of free video lessons, "Statistics Lectures".

### Statistics - Lecture 74

Repeated-Measures ANOVA
One factor with at least two levels, levels are dependent.
By saying that the levels are dependent, it means that they share variability in some way.
The Repeated-Measures ANOVA is almost identical to the One-Way ANOVA, except for one additiona calculation we must perform to account for this shared variability.
Example:
Researchers want to test a new anti-anxiety medication. They measure the anxiety of 7 participants three times: once before taking the medication, once a week after taking the medication, and once two weeks after taking the medication. Anxiety is rated on a scale of 1-10, with 10 being "high anxiety" and 1 being "low anxiety". Are there any differences between the three conditions using alpha = 0.05?

### Statistics - Lecture 75

Factorial ANOVA, Two Independent Factors
Two factors with at least two levels each, levels are independent.
The Factorial ANOVA (with independent factors) is like the One-Way ANOVA, except that now you're dealing with more than one independent variable.

### Statistics - Lecture 76

Factorial ANOVA, Two Dependent Factors
Examples:
Researchers want to compare the anxiety levels of six individuals at two marital states: after they have been divorced, then again after they have gotten married. Anxiety is measured as three times: Week 1, Week 2, and Week 3. Anxiety is rated on a scale of 1-10, with 10 being "high anxiety" and 1 being "low anxiety". Use alpha = 0.05 to conduct your analysis.

### Statistics - Lecture 77

Factorial ANOVA, Two Mixed Factors
Two factors with at least two levels each.
One factor is independent, while the other factor is dependent.
The Factorial ANOVA (with two mixed factors) is a combination of One-Way ANOVA and Repeated-Measures ANOVA.

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