Wilcoxon signed-rank test in SciPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the Wilcoxon signed-rank test used for?

It is a test to compare two related samples to see if their population median ranks differ. It helps check if there is a difference between paired data without assuming normal distribution.

beginner

What kind of data is suitable for the Wilcoxon signed-rank test?

Paired or matched samples where you want to compare differences, especially when data is not normally distributed or sample size is small.

beginner

Which Python library provides the Wilcoxon signed-rank test function?

The 'scipy.stats' module provides the function 'wilcoxon()' to perform the Wilcoxon signed-rank test.

intermediate

What does a low p-value from the Wilcoxon signed-rank test indicate?

It suggests that there is a significant difference between the paired samples, so we reject the idea that their median differences are zero.

intermediate

How do you interpret the test statistic returned by the Wilcoxon signed-rank test?

The test statistic is the sum of ranks of the differences with positive or negative signs. Smaller values indicate stronger evidence against the null hypothesis of no difference.

What type of test is the Wilcoxon signed-rank test?

A Test for correlation between variables

B Non-parametric test for paired samples

C Parametric test for independent samples

D Test for normality of data

The Wilcoxon signed-rank test is a non-parametric test used to compare two related or paired samples.

Which Python function runs the Wilcoxon signed-rank test?

A scipy.stats.ttest_rel()

B scipy.stats.kruskal()

C scipy.stats.mannwhitneyu()

D scipy.stats.wilcoxon()

The function 'wilcoxon()' in scipy.stats performs the Wilcoxon signed-rank test.

When should you use the Wilcoxon signed-rank test instead of a paired t-test?

A When data is not normally distributed

B When samples are independent

C When data is normally distributed

D When sample size is very large

The Wilcoxon signed-rank test is used when the paired data is not normally distributed, unlike the paired t-test which assumes normality.

What does a p-value less than 0.05 in the Wilcoxon test usually mean?

A No difference between samples

B Test is invalid

C Significant difference between samples

D Samples are independent

A p-value less than 0.05 typically means we reject the null hypothesis and conclude there is a significant difference between paired samples.

Which of these is NOT a requirement for the Wilcoxon signed-rank test?

A Samples must be independent

B Differences should be symmetrically distributed

C Data must be paired

D Data can be ordinal or continuous

Samples must be paired, not independent, for the Wilcoxon signed-rank test.

Explain the Wilcoxon signed-rank test and when you would use it.

Think about comparing before and after measurements without assuming normal data.

Describe how to perform the Wilcoxon signed-rank test using scipy and interpret its output.

Focus on the function name, inputs, and what the p-value tells you.