Summary statistics (also known as descriptive statistics) are used to describe the distribution of quantitative variables, in terms of: (i) location (central tendency) such as a mean, median or mode; and (ii) spread (variation) such as standard deviation, percentiles or range.

Frequency distributions are useful for categorical data (for example age groups, or responses to Likert-scale questions). They are easy to explain and interpret for audiences without specialist knowledge and can be presented graphically and in different formats to aid interpretation (e.g. tables, bar/pie charts etc.).

T-tests are used for continuous outcome data to determine if the difference between the means of two groups may be due to chance. The difference in means between the two groups can be reported alongside the associated 95% confidence interval.

Chi square tests (²) are used for categorical data to find out if observed differences between proportions of events in groups is due to chance.

Chi square is used to assess differences in nominal or ordinal outcomes between independent groups.

Independent t-test is used to assess differences in continuous or ratio outcomes between independent groups.

Paired t-tests are used to assess differences in nominal or ordinal outcomes between paired groups (such as measurements taken from the same group pre- and post-intervention)

Linear regression is used for continuous or ratio scale outcome variables

Logistic regression is used for dichotomous outcome variables, e.g. a variable with only two possible values (e.g. yes or no).