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  3. Hypothesis Testing in Python

Exercise

Performing a goodness of fit test

The bar plot of vendor_inco_term suggests that the distribution across the four categories was quite close to the hypothesized distribution. You'll need to perform a chi-square goodness of fit test to see whether the differences are statistically significant.

Recall the hypotheses for this type of test:

\(H_{0}\): The sample matches with the hypothesized distribution.

\(H_{A}\): The sample does not match with the hypothesized distribution.

To decide which hypothesis to choose, we'll set a significance level of 0.1.

late_shipments, incoterm_counts, and hypothesized from the last exercise are available. chisquare from scipy.stats has been loaded.

Instructions 1/2

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  • Using the incoterm_counts and hypothesized datasets, perform a chi-square goodness of fit test on the incoterm counts, n.