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Performing a chi-square test

The chi-square independence test compares proportions of successes of one categorical variable across the categories of another categorical variable.

Trade deals often use a form of business shorthand in order to specify the exact details of their contract. These are International Chamber of Commerce (ICC) international commercial terms, or incoterms for short.

The late_shipments dataset includes a vendor_inco_term that describes the incoterms that applied to a given shipment. The choices are:

  • EXW: "Ex works". The buyer pays for transportation of the goods.
  • CIP: "Carriage and insurance paid to". The seller pays for freight and insurance until the goods board a ship.
  • DDP: "Delivered duty paid". The seller pays for transportation of the goods until they reach a destination port.
  • FCA: "Free carrier". The seller pays for transportation of the goods.

Perhaps the incoterms affect whether or not the freight costs are expensive. Test these hypotheses with a significance level of 0.01.

\(H_{0}\): vendor_inco_term and freight_cost_group are independent.

\(H_{A}\): vendor_inco_term and freight_cost_group are associated.

late_shipments is available, and the following have been loaded: matplotlib.pyplot as plt, pandas as pd, and pingouin.

This exercise is part of the course

Hypothesis Testing in Python

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Hands-on interactive exercise

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

# Proportion of freight_cost_group grouped by vendor_inco_term
props = ____

# Print props
print(props)
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