Chi-squared test in Data Analysis Python - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the Chi-squared test used for?

The Chi-squared test checks if there is a relationship between two categorical variables by comparing observed data with expected data if there was no relationship.

beginner

What are the main inputs needed to perform a Chi-squared test?

You need a contingency table showing counts of observations for combinations of categories from two variables.

intermediate

What does a low p-value in a Chi-squared test indicate?

A low p-value means the observed data is unlikely if the variables were independent, so we may conclude there is an association between the variables.

beginner

What is the null hypothesis in a Chi-squared test?

The null hypothesis says there is no association between the two categorical variables; they are independent.

intermediate

How do you calculate the expected counts in a Chi-squared test?

Expected count for each cell = (row total × column total) ÷ grand total.

What type of data is required for a Chi-squared test?

A Categorical data

B Continuous data

C Time series data

D Text data

The Chi-squared test is designed for categorical data to test relationships between categories.

If the p-value from a Chi-squared test is 0.03, what does this mean at a 0.05 significance level?

A Reject the null hypothesis; variables are likely related

B Fail to reject the null hypothesis; variables are independent

C The test is invalid

D The variables are continuous

A p-value less than 0.05 means we reject the null hypothesis and conclude there is an association.

Which Python library is commonly used to perform a Chi-squared test?

A numpy

B matplotlib

C pandas

D scipy.stats

The scipy.stats library provides the chi2_contingency function for Chi-squared tests.

What does the Chi-squared statistic measure?

A Mean of the data

B Difference between observed and expected counts

C Correlation coefficient

D Variance of the data

The Chi-squared statistic sums the squared differences between observed and expected counts, scaled by expected counts.

What is a contingency table?

A A table of text strings

B A table of continuous values

C A table showing counts of observations for combinations of categories

D A table of dates and times

A contingency table organizes counts of observations by categories of two variables.

Explain the steps to perform a Chi-squared test using Python on a dataset with two categorical variables.

Think about how to prepare data and what the test output means.

Describe what it means if the Chi-squared test shows no significant association between two variables.

Focus on the meaning of independence in this context.