This article is a solid introduction to statistical testing, for beginners, as well as a reference for practitioners. It includes numerous examples as well as illustrations and definitions for concepts such as rejecting the null hypothesis, one sample hypothesis testing, P-values, critical values, and Bayesian hypothesis testing. It has references to additional topics, such as
- What is Ad Hoc Testing?
- What is a Rejection Region?
- What is a Two Tailed Test?
- How to Decide if a Hypothesis Test is a One Tailed Test or a Two Tailed Test.
- How to Decide if a Hypothesis is a Left Tailed Test or a Right-Tailed Test.
- How to State the Null Hypothesis in Statistics.
- How to Find a Critical Value.
- How to Support or Reject a Null Hypothesis.
Picture: When to use ANOVA?
You can read this tutorial here. For specific popular tests, check the following links below, from the same source:
- ANOVA.
- Chi Square Test for Normality
- Cochran-Mantel-Haenszel Test
- F Test
- Granger Causality Test.
- Hotelling’s T-Squared
- KPSS Test.
- What is a Likelihood-Ratio Test?
- Log rank test.
- MANCOVA
- Sequential Probability Ratio Test
- How to Run a Sign Test.
- T Test: one sample.
- T-Test: Two sample.
- Welch’s ANOVA.
- Welch’s Test for Unequal Variances.
- Z-Test: one sample.
- Z Test: Two Proportion
- Wald Test.
For non standard tests, follow this link.
