How to implement the test using the Python API.Īsk your questions in the comments below and I will do my best to answer.ĭid I miss an important statistical test or key assumption for one of the listed tests?.The key assumptions for each test and how to interpret the test result.The types of tests to use in different circumstances, such as normality checking, relationships between variables, and differences between samples.In this tutorial, you discovered the key statistical hypothesis tests that you may need to use in a machine learning project.
Practically ALL assumptions and ALL interpretations are wrong in this cheatsheet. I cannot recommend this, as if a student repeats that on a stat exam or on an interview led by a statistician, one’s likely to fail it. I am messaged regularly by young aspiring data scientists who experienced problems after repeating texts from the internet, that’s why I ask you to not exposing learners to such situations.ġ. Assumptions of the paired t-test are totally wrong, or copy-pasted. Anova is not a test, but OK, let’s pretend I didn’t see it. If you follow that, you may be really surprised doing the post-hocģ. Interpretation of the RM-ANOVA is wrongĤ.
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