A chi-square test is an important statistical test used to analyze contingency tables when sample sizes are large. It compares observed results with expected results, determining whether the difference between observed data and expected data is due to chance or a relationship between the variables. It tells you whether further investigations should be carried out.
This course explores the chi-square test and its applications in the DMAIC roadmap. You’ll learn about the data required for this test and how to conduct it with this data in your hands.
What you’ll learn
The Chi-square hypothesis test for investigating categorical Y and X data.
Where the Chi-square test fits in the DMAIC Roadmap.