Chi–Squares
A researcher wants to investigate if the distribution of M&M colors in a bag matches the distribution claimed by the manufacturer. Which type of chi-square test is most appropriate for this scenario?
Chi-Square Test for Independence
Chi-Square Test for Homogeneity
Chi-Square Test for Goodness of Fit
Two-sample z-test for proportions
A study is conducted to determine if there is a relationship between smoking habits (smoker, non-smoker) and the incidence of lung cancer (yes, no). Which chi-square test should be used?
Chi-Square Test for Goodness of Fit
Chi-Square Test for Independence
Chi-Square Test for Homogeneity
One-sample z-test for proportions
A researcher wants to compare the distribution of political affiliations (Democrat, Republican, Independent) among three different age groups. Which chi-square test is most appropriate?
Chi-Square Test for Goodness of Fit
Chi-Square Test for Independence
Chi-Square Test for Homogeneity
Matched Pairs t-test
What are the necessary conditions that must be met before conducting a chi-square test?
Normality and equal variances
Randomness and independence
Randomness and Large Counts
Equal sample sizes and equal means
In a chi-square test, you have a two-way table with expected counts. Which of the following scenarios would violate the conditions for a valid test?
All expected counts are greater than 10.
All expected counts are greater than 5.
One expected count is less than 5.
The sample size is less than 30.
A researcher is performing a chi-square test and finds that several of the expected counts are less than 5. What impact could this have on the validity of the test, and what are some potential remedies?
The test is still valid as long as the overall sample size is large; no remedies are needed.
The test results may be unreliable due to the violation of the large counts condition; potential remedies include combining categories or increasing the sample size.
The test will always be invalid, and there are no remedies available.
The p-value will always be 0.
A researcher is investigating whether there is a relationship between gender and preference for a particular brand of coffee. What is the null hypothesis for a chi-square test of independence in this scenario?
There is an association between gender and coffee brand preference.
Gender causes a change in coffee brand preference.
There is no association between gender and coffee brand preference.
Coffee brand preference causes a change in gender.

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A market researcher claims that the distribution of car colors purchased by customers is different from the distribution reported last year. Formulate the null and alternative hypotheses.
H0: The distribution of car colors is the same as last year; Ha: The distribution of car colors is different from last year.
H0: The distribution of car colors is different from last year; Ha: The distribution of car colors is the same as last year.
H0: Car color preference is independent of the year; Ha: Car color preference is dependent on the year.
H0: There is no difference in the total number of cars sold; Ha: There is a difference in the total number of cars sold.
A chi-square test yields a p-value of 0.03. Using a significance level of , what conclusion can be drawn?
Fail to reject the null hypothesis.
Reject the null hypothesis.
Accept the null hypothesis.
The test is invalid.
In a study examining the relationship between exercise habits and weight management, a chi-square test yields a p-value of 0.12. Interpret this result in the context of the research question.
There is strong evidence of a relationship between exercise habits and weight management.
There is no evidence of a relationship between exercise habits and weight management.
Exercise habits cause changes in weight management.
Weight management causes changes in exercise habits.