Understanding Chi Square Tests

What is the primary purpose of a Chi Square test?

• To compare means between two groups

• To test the association between categorical variables

• To predict a continuous outcome

• To measure the correlation between two variables

Which of the following is a key assumption of the Chi Square test?

• The data must be normally distributed

• The data must be continuous

• The expected frequency in each cell of the contingency table should be at least 5

• The sample size must be less than 30

In a Goodness of Fit test, what is being tested?

• Whether two categorical variables are independent

• Whether the observed frequencies differ from the expected frequencies

• Whether the means of two groups are equal

• Whether the variance of a sample is equal to a known value

What is a contingency table used for in Chi Square tests?

• To display the distribution of a single variable

• To show the relationship between two categorical variables

• To calculate the mean and standard deviation

• To perform linear regression analysis

Which of the following is NOT an assumption of the Chi Square test?

• Observations must be independent

• The sample data must be randomly selected

• The data must be ordinal

• The expected frequency in each category should be at least 5

How is the Chi Square statistic calculated?

In a Chi Square test of independence, what does a significant result indicate?

• The two variables are independent

• The two variables are dependent

• The sample size is too small

• The data is normally distributed

What is the degree of freedom for a Chi Square test with a contingency table of size 3x4?

• 6

• 7

• 8

• 9

Which of the following is a common use of the Chi Square Goodness of Fit test?

• Testing if a die is fair

• Testing if two variables are correlated

• Testing if a sample mean is equal to a population mean

• Testing if a sample variance is equal to a population variance

When interpreting Chi Square results, what does a p-value less than 0.05 typically indicate?

• There is no significant difference

• There is a significant difference

• The test is invalid

• The sample size is too large