What are the key differences between a t-test and a chi-square test, and how do these differences impact their respective applications in statistical analysis?

Answer 1

A t-test is used to compare means between two groups, while a chi-square test is used to determine if there is a relationship between two categorical variables. The key difference is in the type of data being analyzed - t-tests are for continuous data, while chi-square tests are for categorical data. This impacts their applications as t-tests are used for comparing means, such as in experiments with control and experimental groups, while chi-square tests are used for analyzing relationships, such as in surveys or contingency tables.