A series of free Statistics Lectures with lessons, examples & solutions in videos.
This is page twenty-four of the series of free video lessons, “Statistics Lectures”. These lectures continue the discussion on ANOVA - analysis of variance, covering repeated-measures ANOVA, factorial ANOVA with two independent factors, two dependent factors and two mixed factors.
22: More Samples t-Test
23: Introduction To ANOVA & One-Way ANOVA
25: Chi-Square Test
26: Mann-Whitney, Wilcoxon, Kruskal-Wallis & Friedman Tests
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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.
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?
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.
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.
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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