1. STATISTICAL TEST

2. Two types of statistical test:
Parametric tests:
Based on assumption that the data have
certain characteristics or "parameters":
Results are only valid if
(a) the data are normally distributed;
(b) the data show homogeneity of variance;
(c) the data are measurements on an interval or ratio scale.
group 1: M = 8.19 (SD= 1.33),
group 2: M = (SD = 9.18)

3. Nonparametric tests:
Make no assumptions about the data's characteristics.
Use if any of the three properties below are true:
(a) the data are not normally distributed (e.g. skewed);
(b) the data show inhomogeneity of variance;
(c) the data are measured on an ordinal scale (ranks).

4. Examples of parametric tests and their non-parametric equivalents:
Parametric test: Non-parametric counterpart:
Pearson correlation Spearman's correlation
(No equivalent test) Chi-Square test
Independent-means t-test Mann-Whitney test
Dependent-means t-test Wilcoxon test
One-way Independent Measures
Analysis of Variance (ANOVA) Kruskal-Wallis test
One-way Repeated-Measures
ANOVA Friedman's test