Hypothesis Testing Cheat Sheet

In this article, we give you statistics Hypothesis Testing Cheat Sheet rules and steps for understanding examples of the Null Hypothesis and the Alternative Hypothesis of the key hypothesis tests in our Lean Six Sigma Green Belt and Lean Six Sigma Black Belt courses.

You can use hypothesis tests to challenge whether some claim about a population is proven to be statistically true (meaning that the data proves that the claim through data). For example, a claim that “site A” in a financial company closes loans faster than “site B”. Another example may be that “shift 1” is performing better than “shift 2”.

I can’t tell you how many times I have sat in management meetings where I have heard leaders asking “why one department was performing better than another” because they could visually see a difference between the two departments. But when we compared the data from the two departments in a hypothesis test, we discovered that there was no statistically significant difference between the two departments. I have seen people fired for a perceived visual difference when there was no statistically significant difference.

Hypothesis testing rules is a formal statistical technique to decide objectively whether there is a significant statistical difference.

This article is a Hypothesis Testing Cheat Sheet” for those in our Lean Six Sigma Green Belt and Lean Six Sigma and Black Belt courses to quickly identify the Null Hypothesis and the Alternative Hypothesis for each Hypothesis Test.

Hypothesis Testing
statistics hypothesis testing cheat sheet
Hypothesis Testing
hypothesis testing examples

What did you think? Did this article help you in your statistical analysis using hypothesis testing steps? Please share your thoughts in the comments below.

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