# GraphPad - FAQ 1790 - Choosing a statistical test

This approach consists of four steps: (1) state the hypotheses, (2) formulate an analysis plan, (3) analyze sample data, and (4) interpret results. State the Hypotheses, suppose that Variable A has r levels, and.
The sample problem at the end of the lesson considers this example. When to Use Chi-Square Test for Independence, the test procedure described in this lesson is appropriate when the following conditions are met: If sample data are displayed in a contingency table, the expected frequency count for each cell of the table is at least 5.
For example, in an election survey, voters might be classified by gender (male or female) and voting preference (Democrat, Republican, or Independent). We could use a chi-square test for independence to determine whether gender is related to voting preference.
H0: Variable A and Variable B are independent. Ha: Variable A and Variable B are not independent. The alternative hypothesis is that knowing the level of, variable A can help you predict the level of, variable B.
This lesson explains how to conduct a chi-square test for independence. The test is applied when you have two categorical variables from a single population. It is used to determine whether there is a significant association between the two variables.
The analysis plan describes how to use sample data to accept or reject the null hypothesis. The plan should specify the following elements. Significance level. Often, researchers choose significance levels equal to 0.01, 0.05, or 0.10; but any value between
Variable B has c levels. The null hypothesis states that knowing the level of, variable A does not help you predict the level of. Variable B. That is, the variables are independent.