You’ve got data, you’ve got a hypothesis, you even gathered the courage to test it. But how do you choose the right test? Well, really you should have thought about this before you collected the data. Maybe you did and maybe you didn’t. I won’t judge (ok, maybe a little). Instead, I’ll offer you a handy cheat sheet that could help you navigate through the various tests and their assumptions whenever you need to do that.
When I just started my PhD program, I had very little knowledge of applied statistics in behavioural sciences. I had a computer science degree and could do probability, but was not friends with t-tests and ANOVAs. Thankfully, statistics courses were a degree requirement and I enjoyed them so much that I ended up teaching and tutoring undergraduates in the following years.
This cheat sheet came about while I was taking the introductory univariate statistics course back in 2009. It took a significant number of neurons to remember all the tests and their assumptions, so I decided to follow Einstein’s advice and “Never memorize something that you can look up.”
Yellow blocks show the questions to answer / decisions to make about your data, orange blocks show transformations required to use the tests and blue blocks show the tests and their assumptions. Don’t forget, this cheat sheet is just a start and is not a complete guide. Once it helped you pick a test, deep dive into the test’s details in your stats book or online resources.