Statistics for Research: How to Choose an Appropriate Statistical Test

Hello! Stat Hacks here!

In this series, I will be blogging about some tips to choose the appropriate statistical test for your analysis. These tips are gathered from both my experience working as a statistician, and also from my undergraduate projects.

In each post, I will be highlighting some of the major misconcpetions that people usually make about the tests, and also highlight why an alternative test is better than the initially chosen one.

The contents of this series is as follows:

1. t-test vs paired t test: Why you should use a paired t-test when you can

2. z-test for Proportion vs Independent Samples t-test: Don’t use use the wrong test

3. Analysis of Variance (ANOVA) vs t-Test: Differences, Uses, and Examples

4. Equivalence Testing vs t-Test: Why Failing to Reject H₀ Doesn’t Mean H₀ Is True

5. Linear Regression vs t-test: When to choose what?

6. Linear Regression vs Logistic Regression

7. Interactive Statistical Test Recommender (Free Resource)

8. Guided Tutorials on Conducting Statistical Tests (Paid Resource)

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