Introduction to ANOVA
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Questions
- What null hypothesis is tested by ANOVA?
- What are the uses of ANOVA?
What is ANOVA?
- Analysis of Variance (ANOVA) is a statistical method used to compare two or more means
- Inferences about means are made by analyzing variance (therefore it is not called analysis of mean)
- ANOVA is used to test general rather than specific differences among means
Smiles and Leniency Example
- Let us investigate types of smiles on the leniency
- Types of smiles: neutral, false, felt, miserable
The results from the Tukey hsd test (Six Pairwise Comparisons):
Comparison | Mi-Mj | Q | p |
---|---|---|---|
False - Felt | 0.46 | 1.65 | 0.649 |
False - Miserable | 0.46 | 1.65 | 0.649 |
False - Neutral | 1.25 | 4.48 | 0.010 |
Felt - Miserable | 0.00 | 0.00 | 1.000 |
Felt - Neutral | 0.79 | 2.83 | 0.193 |
Miserable - Neutral | 0.79 | 2.83 | 0.193 |
- Notice that the only significant difference is between the False and Neutral conditions.
- ANOVA tests the non-specific null hypothesis that all four populations means are equal
μfalse = μfelt = μmiserable = μneutral
- This non-specific null hypothesis is sometimes called the omnibus null hypothesis
- When the omnibus null hypothesis is rejected, the conclusion is that at least one population mean is different from at least one other mean
- ANOVA does not reveal which means are different from which
- It offers less specific information than the Tukey hsd test
- The Tukey hsd is therefore preferable to ANOVA in this situation
Why to use ANOVA instead of HSD Tukey
- There are complex types of analyses that can be done with ANOVA and not with the Tukey test
- ANOVA is by far the most commonly-used technique for comparing means
- Is important to understand ANOVA in order to understand research reports.
Questions