Minitab offers several analyses to summarize and perform tests on count and categorical data.
To determine whether two categorical variables are associated, use a chi-square test for association. For example, determine whether the sales for different colors of cars depends on the city where they are sold. Your data can be arranged as columns of raw data, or summarized in a contingency table. In Minitab, choose
.To summarize data for multiple groups or categories, or test for association between two categorical variables, use a cross tabulation and chi-square analysis. For example, show how many defective parts were created on different production lines, during each shift. Your data can be arranged as columns of raw data, or summarized as frequency data, or summarized in a contingency table. In Minitab, choose
.To determine whether the proportions in each category differ from the expected proportions, use a chi-square goodness-of-fit test. For example, a researcher wants to determine whether the proportions of people who prefer certain colors of shoes agree with specified values. Your data can be arranged as columns of raw data, or summarized as frequency data. In Minitab, choose
.To summarize data for groups that are formed by two or more categorical variables, in Minitab, choose
. Your data can be arranged as columns of raw data, or summarized as frequency data.For more information on raw, frequency, and summarized data, go to Worksheet arrangements for data types