Abstract
BACKGROUND:
Hypothesis tests are statistical tools widely used for assessing whether or not there is an association between two or more variables. These tests provide a probability of the type 1 error (p-value), which is used to accept or reject the null study hypothesis.
OBJECTIVE:
To provide a practical guide to help researchers carefully select the most appropriate procedure to answer the research question. We discuss the logic of hypothesis testing and present the prerequisites of each procedure based on practical examples.
Keywords:
Data analysis; Association; Epidemiology and biostatistics; Hypothesis testing; Statistical methods and procedures