Sometimes, the most difficult part of conducting an analysis is determining which analysis to apply. For this reason, I made some practice questions below to help students with determining the correct analysis to apply in various circumstances.

Some questions may have multiple answers, all of which may or may not be listed below. Keep that in mind if you think a question could have a different answer than the one listed below – because it might! As always, please email me at MHoward@SouthAlabama.edu if you have any questions.

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Questions

1.) What analysis would you conduct to determine whether company size and company R&D expenditures significantly predict company revenue? Assume that all variables are measured on a continuous scale.

2.) What analysis would you conduct to determine the general relations between company size, company R&R expenditures, and company revenue? Assume that all variables are measured on a continuous scale.

3.) What analysis would you conduct to determine whether company R&R expenditures significantly relate to company revenue while controlling for company size? Assume that all variables are measured on a continuous scale.

4.) What analysis would you conduct to determine whether there is an interaction between company size and company R&D expenditures in predicting company revenue? Assume that all variables are measured on a continuous scale.

5.) What analysis would you conduct to determine whether the effect of company size on company revenue is due to (or explained by) company R&D expenditures? Assume that all variables are measured on a continuous scale.

6.) What analysis would you conduct to determine whether the relation of company size and company revenue is best described by a single curve? Assume that all variables are measured on a continuous scale.

7.) What analysis would you conduct to assess the internal consistency of a job satisfaction scale?

8.) What analysis would you conduct to determine whether employees at Factory A have a higher job satisfaction than employees at Factory B? Assume that job satisfaction is measured on a continuous scale.

9.) What analysis would you conduct to determine whether employees at Factory A have a job satisfaction score different than 10? Assume that job satisfaction is measured on a continuous scale.

10.) What analysis would you conduct to determine whether employees’ job satisfaction differs between Factory A, B, and C? Assume that job satisfaction is measured on a continuous scale.

11.) What analysis would you conduct to determine whether employees’ job satisfaction differs between Factory A, B, and C as well as Locations 1, 2, and 3? Assume that job satisfaction is measured on a continuous scale.

12.) What analysis would you conduct to determine whether the number of employees within your sample differs between Factory A, B, and C?

13.) What analysis would you conduct to determine whether the number of employees within your sample differs between Factory A, B, and C as well as Locations 1, 2, and 3?

14.) What analysis would you run to determine whether employees’ job satisfaction differs between Factory A and B as well as whether employees’ conscientiousness relates to their job satisfaction? Assume that job satisfaction and conscientiousness are measured on a continuous scale.

15.) What analysis would you conduct to determine whether students’ well-being differs between Classroom A, B, and C as well as gender? Assume that well-being is measured on a continuous scale.

16.) What analysis would you conduct to determine whether students in Class A have a well-being score different than 10? Assume that well-being is measured on a continuous scale.

17.) What analysis would you conduct to determine whether agreeableness significantly relates to well-being while controlling for number of friendships? Assume that all variables are measured on a continuous scale.

18.) What analysis would you conduct to determine the general relations between agreeableness, number of friendships, and well-being? Assume that all variables are measured on a continuous scale.

19.) What analysis would you conduct to assess the internal consistency of a well-being scale?

20.) What analysis would you run to determine whether students’ well-being differs between Classroom A and B as well as whether students’ number of friendships relates to their well-being? Assume that agreeableness and well-being are measured on a continuous scale.

21.) What analysis would you conduct to determine whether the number of students within your sample differs between Classroom A, B, and C?

22.) What analysis would you conduct to determine whether students’ well-being differs between Classroom A, B, and C? Assume that well-being is measured on a continuous scale.

23.) What analysis would you conduct to determine whether there is an interaction between agreeableness and number of friendships in predicting well-being? Assume that all variables are measured on a continuous scale.

24.) What analysis would you conduct to determine whether agreeableness and number of friendships significantly predict well-being? Assume that all variables are measured on a continuous scale.

25.) What analysis would you conduct to determine whether students in Class A have a higher well-being than Students in Class B? Assume that well-being is measured on a continuous scale.

26.) What analysis would you conduct to determine whether the relation of agreeableness and well-being is best described by a single curve? Assume that all variables are measured on a continuous scale.

27.) What analysis would you conduct to determine whether the number of students within your sample differs between Classroom A, B, and C?

28.) What analysis would you conduct to determine whether the effect of agreeableness on well-being is due to (or explained by) number of friendships? Assume that all variables are measured on a continuous scale.

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Answers

1.) Regression

2.) Correlation

3.) Partial Correlation or Regression

4.) Moderation with Regression

5.) Mediation

6.) Quadratic Regression

7.) Cronbach’s alpha

8.) Two-Sample T-Test

9.) One-Sample T-Test

10.) One-Way ANOVA

11.) Two-Way ANOVA

12.) Chi-Square

13.) Chi-Square

14.) Dummy-Coded Regression

15.) Two-Way ANOVA

16.) One-Sample T-Test

17.) Partial Correlation or Regression

18.) Correlation

19.) Cronbach’s alpha

20.) Dummy-Coded Regression

21.) Chi-Square

22.) One-Way ANOVA

23.) Moderation with Regression

24.) Regression

25.) Two-Sample T-Test

26.) Quadratic Regression

27.) Chi-Square

28.) Mediation