ANOVA and multiple comparisons
ANOVA is a global test. If the hypothesis that all means are equal is rejected, ANOVA produces no detailed explanation as to why it rejected it.
The ANOVA method provides an integrative approach to estimating variance components, but it is not without problems (i.e.
One-Factor ANOVA
Purpose:
Test for Equal Means Across Groups
One factor analysis of variance (Snedecor and Cochran, 1989) is a special case of analysis of variance (ANOVA), for one factor of interest, and a generalization of the two-sample t-test.
The authors conducted standard ANOVAs on this data with hemisphere, experiment number, number of possible responses and information value of the cues as factors.
Analysis of variance (ANOVA)
Chi-square test
Correlation
Factor analysis
Mann-Whitney U
Mean square weighted deviation (MSWD)
Pearson product-moment correlation coefficient
Regression analysis
Spearman's rank correlation coefficient ...
The R square must be bigger than 0.80
The significant F (from ANOVA) must be smaller than 0.05
The absolute value of t-statistics must be larger than 1.96 for =0.05 and must larger than 1.645 for =0.10 ...
 See also: Distribution, Variance, Regression, Data mining, Normal distribution
  
|
RSS
