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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 TestingHypothesis testing definition A statistical hypothesis test ... Cheat Sheet” for those in our Lean Six Sigma Green BeltThe Six Sigma Green Belt is a certificate that professionals... and Lean Six SigmaSix Sigma Definition: Six Sigma is a set of techniques and t...Six Sigma Green BeltThe Six Sigma Green Belt is a certificate that professionals... and Black Belt courses to quickly identify the Null Hypothesis and the Alternative Hypothesis for each Hypothesis TestHypothesis testing definition A statistical hypothesis test ....
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.
Excellent sharing, Kevin! Just a reminder: you reject Ho when P ≤ 0.05.
Ramiro,
I’m compelled to provide a correction to your statement. The best way to keep it straight is the following saying:
“if the p is low Ho must go (Reject the Null Hypothesis)” p .05
I hope that helps.
Robert,
I am compelled to say that as the saying goes “If P- is low Ho must go (reject the null hypothesis)” is the same as, If P is less than your alpha, reject Ho (this is the null hypothesis).” I do not see anything different. I hope that it helps.
Multiple tests very well simplified in a concise way! Excellent.
You may like to consider adding a few more things if appropriate.
On the first table, the Tests of Variance can be separated as One-variance test (chi-square test), Two-variance test (F-test) from more than two variance tests.
On second table, chi-square test can be expanded to include test of more than two proportions and goodness-of-fit test.
Dhruv, excellent point. I will have my team revise.