choosing a statistical test Flashcards
Levels of measurement
quantitative data can be classified into types or levels of measurement, such as nominal, ordinal and interval
Statistical tests
used in psychology to determine whether a significant difference or correlation exists (and consequently, whether the null hypothesis should be rejected or retained).
8 statistical tests
- Chi-squared
- Mann-Whitney
- Pearsons r
- Related t-test
- sign test
- Spearman’s rho
- Unrelated test
- Wilcoxon
Chi-Squared
a test for an association (difference or correlation) between 2 variables or conditions. Data should be nominal level using an unrelated (independent) design.
Mann-Whitney
a test for a significant difference between two sets of scores. Data should be at least ordinal level using an unrelated design (independent groups).
Pearson’s r
a parametric test for correlation when data is at interval level
Related t-test
a parametric test for difference between 2 sets of scores. Data must be interval with a related design, i.e. repeated measures or matched pairs
Sign test
a statistical test used to analyse the difference in scores between related items (e.g. the same participant tested twice). Data should be nominal or better.
Spearman’s rho
a test for correlation when data is at least ordinal level
Unrelated t-test
a parametric test for difference between two sets of scores. Data must be interval with an unrelated design, i.e. independent groups
Wilcoxon
a test for a significant difference between 2 sets of scores. Data should be at least ordinal level using a related design (repeated measures).
Difference or correlation?
- first thing to consider when deciding which statistical test to use related to the aim or purpose of the investigation - looking for difference or correlation?
- should be obvious in the wording of hypothesis
step 2 of choosing a statistical test
experimental design
step 3 of choosing a statistical test
- levels of measurement
- quantitative data can be divided into different levels of measurement and this is the third factor influencing the choice of statistical test — nominal, ordinal and interval
Nominal data
data represented in form of categories
- discrete -> one item can only appear in one of the categories.