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Chi-square test

In this exercise, you will be working with the Olympics dataset. Here, we're going to look at the sex ratio of the American Olympic squads. Is a bias present? That is to say, does the ratio of male to female athletes significantly depart from 50-50? To test this, you'll need to perform a Chi-square test on the Sex data. Data on American athletes is provided as athletes. pandas, and plotnine have been loaded into the workspace as pd and p9.

This exercise is part of the course

Performing Experiments in Python

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Exercise instructions

  • Using value_counts(), extract the number of individuals of each Sex from athletes, saving the result as sexratio.
  • Perform a chisquare() test on sexratio and print the result.
  • Compare the p-value to the given alpha and print the message.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Extract sex ratio
sexratio = athletes[____].____

# Perform Chi-square test
chi= stats.____(____)
print(____)

# Test significance
alpha= 0.05
if ____ < alpha:
    print("Difference between sexes is statistically significant")
else:
    print("No significant difference between sexes found")
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