This page list the core topics used in quantitative research. Each group has a pull down menu with a fuller list and the link to the relevant page for those resources. Check the descriptions to understand when each test is appropriate to use, but if you are still not sure, use our Test chooser resources

*Note: We are still updating our website so not all resources may be available yet. *** **

Are you comparing means of different groups of subjects?

**One-way ANOVA**

One categorical/grouping variable**Two-way ANOVA**

Two categorical/grouping variables**ANCOVA**

ANOVA controlling for a continuous variable**MANOVA**

Testing multiple related dependent variables by group**Kruskal-Wallis**

Non-parametric one way ANOVA

Repeated measures are measurements of the same variable on the same subject at different time points or under different conditions and can be referred to as within groups.

**One-way repeated measures ANOVA**

3+ measurements of the same variable on each subject**Friedman**

Use if the repeated measurement is ordinal or assumptions of the one-way repeated measures not met**Mixed between-within ANOVA**

Use if you are comparing different groups and repeated measurements

How to produce relevant summary statistics and charts to go with tests such as t-tests and ANOVA

How to produce relevant summary statistics and charts to go with tests such as Chi-squared

**Chi-squared test of association**

For testing for an association between TWO categorical variables

**Chi-squared goodness of fit**

One categorical variable and looking to see if it fits a particular probability distribution

**Scatterplots**

Visualising the strength of relationships between continuous variables**Pearson's correlation**

Assessing strength of relationships between normally distributed continuous variables**Spearman's correlation**

Assessing strength of relationships between skewed or ordinal variables

**Simple linear regression**

One continuous independent variable**Multiple linear regression**

Multiple continuous or binary independent variables

Logistic regression is used when you want to test one or more predictors of a binary dependent variable.

Used to compare two groups when the dependent variable is ordinal or assumptions of the independent t-test are not met

Used to compare two measurements of the same variable when the dependent variable is ordinal or assumptions of the paired t-test are not met

Used to compare 3+ groups when the dependent variable is ordinal or assumptions of one-way ANOVA are not met

Used to compare 3+ measurements of the same variable when the dependent variable is ordinal or assumptions of repeated measures ANOVA are not met. Also used to compare rankings.

**One sample t-test**

Testing a sample mean against a set value

**Paired t-test**

Two measurements of the same continuous variable**Wilcoxon signed rank**

Two measurements of the same skewed or ordinal variable

**Summarising continuous data**

Summary statistics and graphs for continuous dependent variables**Independent t-test**

Comparing the means of two different groups**Mann-Whitney/ Wilcoxon rank sum**

Comparing two different groups for ordinal variables