A researcher collected data on the primary type of television programming watched based on education levels. The contingency table is as follows:Among respondents with only a high school diploma, 43 primarily watch news programming, 60 primarily watch reality TV, and 48 primarily watch other types of TV programming. Among respondents with an associate's degree, 29 primarily watch news programming, 58 primarily watch reality TV, and 58 primarily watch other types of TV programming. Among respondents with a bachelor's degree, 36 primarily watch news programming, 38 primarily watch reality TV, and 30 primarily watch other types of TV programming. ... Which test is used to determine if there is a significant difference among the categories of data?

This test is designed to compare the means of two groups and is applicable primarily for continuous data rather than categorical data. Since the question involves counts of respondents within categories rather than comparison of means, a t-test is not suitable for this scenario.

While this test also involves categorical data, it is specifically used to determine if different populations (or groups) have the same distribution of a categorical variable. In this case, we are not comparing different populations but rather examining the relationship within a single population across categories, making this test inappropriate.

This test evaluates if the observed frequency distribution of a single categorical variable fits a specified distribution. Since the question involves the relationship between two categorical variables, a goodness-of-fit test is not applicable in determining the association between education levels and television programming preferences.