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# Choosing a non-parametric test

Explanations > Social ResearchAnalysis > Choosing a non-parametric test

## Choosing the test

Use the table below to choose the test. See below for further details.

How many separate samples?

1

How many scores for each subject?

1

 How many measurement categories? 2 Binomial test 2+ Chi-square test for goodness of fit

2

 Can difference scores be ranked? Y Wilcoxon test N Sign test

2

Matched samples? (N = independent)

Y

 Can difference scores be ranked? Y Wilcoxon test N Sign test

N

 Can scores be ranked with few tied values? (independent samples only) Y Median test Y Mann-Whitney test N Chi-square test for independence
>2
 Can scores be ranked with few tied values? (independent samples only) Y Median test N Chi-square test for independence N Krushkal-Wallas test

## Discussion

Non-parametric tests do not assume an underlying Normal (bell-shaped) distribution.

There are two general situations when non-parametric tests are used:

1. Data is nominal or ordinal (where means and variance cannot be calculated).
2. The data does not satisfy other assumptions underlying parametric tests.

Parametric vs. non-parametric tests

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