Goodness of fit evaluation in SciPy - Mini Project: Build & Apply

Goodness of Fit Evaluation with SciPy

📖 Scenario: You are a data analyst working with a small dataset of observed counts from a survey. You want to check if these observed counts fit a theoretical expected distribution using a goodness of fit test.

🎯 Goal: Build a Python program that uses SciPy to perform a chi-square goodness of fit test comparing observed data to expected data.

📋 What You'll Learn

Create a list called observed_counts with exact values [18, 22, 20, 15, 25]

Create a list called expected_counts with exact values [20, 20, 20, 20, 20]

Use scipy.stats.chisquare to perform the goodness of fit test

Print the chi-square statistic and p-value with clear labels

💡 Why This Matters

🌍 Real World

Goodness of fit tests are used in surveys, quality control, and scientific experiments to check if data matches expected patterns.

💼 Career

Data analysts and scientists use these tests to validate models and assumptions about data distributions.

1

Create observed data list

Create a list called observed_counts with these exact values: [18, 22, 20, 15, 25].

SciPy

# Create the observed counts list
# Your code here

Need a hint?

Use square brackets to create a list and separate numbers with commas.

2

Create expected data list

Create a list called expected_counts with these exact values: [20, 20, 20, 20, 20].

SciPy

observed_counts = [18, 22, 20, 15, 25]
# Create the expected counts list
# Your code here

Need a hint?

Use the same list syntax as before to create the expected counts list.

3

Perform chi-square goodness of fit test

Import chisquare from scipy.stats and use it to perform a chi-square test comparing observed_counts and expected_counts. Store the result in a variable called chi2_result.

SciPy

observed_counts = [18, 22, 20, 15, 25]
expected_counts = [20, 20, 20, 20, 20]
# Import chisquare and perform the test
# Your code here

Need a hint?

Use chisquare(f_obs=observed_counts, f_exp=expected_counts) to run the test.

4

Print chi-square statistic and p-value

Print the chi-square statistic and p-value from chi2_result with labels: Chi-square statistic: and p-value:.

SciPy

from scipy.stats import chisquare

observed_counts = [18, 22, 20, 15, 25]
expected_counts = [20, 20, 20, 20, 20]

chi2_result = chisquare(f_obs=observed_counts, f_exp=expected_counts)
# Print the chi-square statistic and p-value
# Your code here

Need a hint?

Use print(f"Chi-square statistic: {chi2_result.statistic}") and similarly for p-value.