# Statistical tests – interactive tool

By Data Tricks

## Which statistical test?

Choosing which statistical test to use can be confusing, with a seemingly endless list of options depending on whether you have interval or nominal data, paired, unpaired or parametric. The interactive tool on this page has been developed to help you choose an appropriate statistical test.

## How to use this tool

The tool asks a set of questions about your objective and your data. Select the answer that best matches your problem and the tool will recommend an appropriate statistical test. Click the link at the end for instructions on how to perform the test or calculation in R.
Instructions are being updated regularly so please bear with us if the instructions for a particular test are not available.

## What are you assessing?

### Differences between samples

I have split my data into groups and want to compare those groups

### Relationships between variables

I am looking for links between variables

## How many samples do you have?

### One sample

I have a single sample and I want to see if the average is different from a fixed value

### Two samples

I have two samples and want to see the differences between them

### Multiple samples

I have more than 2 samples and want to see the differences between them (note if your independent variable has more than 2 levels then you effectively have >2 samples)

## What's the measurement scale of the variable you want to test?

### Interval

Your scale has an order and known differences between the values, eg. cm to measure distance, or height

### Ordinal

Your scale has an order but different distances between values, eg. a rank order

### Nominal

Your measure has no quantitative value, eg. gender

## What is the distribution of your data?

### Yes

My samples are paired

### No

My samples are not paired

## What's the measurement scale of the variable you want to test?

### Interval

Your scale has an order and known differences between the values, eg. cm to measure distance, or height

### Ordinal

Your scale has an order but different distances between values, eg. a rank order

### Nominal

Your measure has no quantitative value, eg. gender

## What's the measurement scale of the variable you want to test?

### Interval

Your scale has an order and known differences between the values, eg. cm to measure distance, or height

### Ordinal

Your scale has an order but different distances between values, eg. a rank order

### Nominal

Your measure has no quantitative value, eg. gender

## What is the distribution of your data?

### Yes

My samples are matched

### No

My samples are not matched

## What's the measurement scale of the variable you want to test?

### Interval

Your scale has an order and known differences between the values, eg. cm to measure distance, or height

### Ordinal

Your scale has an order but different distances between values, eg. a rank order

### Nominal

Your measure has no quantitative value, eg. gender

## What's the measurement scale of the variable you want to test?

### Interval

Your scale has an order and known differences between the values, eg. cm to measure distance, or height

### Ordinal

Your scale has an order but different distances between values, eg. a rank order

### Nominal

Your measure has no quantitative value, eg. gender

## Do you have dependent and independent variables?

### Yes

There are clearly defined dependent and independent variables

### No

The variables are interdependent

## What's the measurement scale of your dependent variable?

### Interval

Your scale has an order and known differences between the values, eg. cm to measure distance, or height

### Ordinal

Your scale has an order but different distances between values, eg. a rank order

### Nominal

Your measure has no quantitative value, eg. gender

## What's the measurement scale of your variables?

### All are interval

All variables are on an interval scale

### Interval and/or ordinal

I have interval and/or ordinal variables but no nominal variables

### All are nominal

All my variables are nominal

## Result

### Kruskal-Wallis test

Please note that your first comment on this site will be moderated, after which you will be able to comment freely.