Understanding Research Methods: ANOVA, Design, and Analysis

1. Stats/Methods II JEOPARDY

2. Jeopardy Repeated-Measures ANOVA Compare & Contrast Factorial Design Factorial ANOVA Surprise $100 $100 $100 $100 $100 $200 $200 $200 $200 $200 $300 $300 $300 $300 $300 $400 $400 $400 $400 $400 $500 $500 $500 $500 $500

3. Compare & Contrast--$100 • In a between-subjects design, each participant contributes ___ score(s), but in a within-subjects design, each participant contributes _______ score(s). • answer

4. Compare & Contrast--$200 • This part of the F-ratio is the same for both between- and within-subjects designs. • answer

5. Compare & Contrast--$300 • The additional preliminary calculation required for a within-subjects design. • answer

6. Compare & Contrast--$400 • When individual differences are large, this design is more likely to miss a significant treatment effect when one really exists. • answer

7. Compare & Contrast--$500 • The denominators for a between- and within-subjects ANOVA, respectively. • answer

8. Repeated-M ANOVA--$100 • The consistent performance (individual differences) of a subject is represented by this SS. • answer

9. Repeated-M ANOVA--$200 • Because the same participant serves in all treatments, individual differences are automatically removed as a source of variability in this SS. • answer

10. Repeated-M ANOVA--$300 • In a repeated measures design, if F(3, 24) = 4.67, then each participant serves in ___ treatment conditions. • answer

11. Repeated-M ANOVA--$400 • When figuring SSs in a within-subjects design, ___ is often referred to as the residual term because it is the variability left after ___ is subtracted from it. • answer

12. Repeated-M ANOVA--$500 • In a repeated-measures design, if k = 5 and dfTotal = 40, then dfWithin Treatments = ___. • answer

13. Factorial Design--$100 • μA1 = μA2 assumes there will be no _________. • answer

14. Factorial Design--$200 • The major advantage of conducting a factorial experiment is the ability to assess this. • answer

15. Factorial Design--$300 • The two values you need to look up the critical value of FAxB. • answer

16. Factorial Design--$400 • In a factorial design, these effects may not accurately represent the mean differences between individual treatment conditions. • answer

17. Factorial Design--$500 • The analysis that looks for mean differences within an individual column (or row) of the treatment matrix. • answer

18. Factorial ANOVA--$100 • The number of hypothesis tests included in a two-factor ANOVA. • answer

19. Factorial ANOVA--$200 • In a factorial experiment, this type of variability is partitioned into 3 components. • answer

20. Factorial ANOVA--$300 • When looking at an AB treatment matrix, the numbers that enter into tests of main effects. • answer

21. Factorial ANOVA--$400 • In a 4x2 factorial design, the number of treatment totals entering into the analysis for the interaction. • answer

22. Factorial ANOVA--$500 • In order to graph the interaction, calculate _____ and plot them. Lines that _______ indicate the possibility of an interaction. • answer

23. Surprise--$100 • In plotting the interaction, parallel lines indicate. • answer

24. Surprise--$200 • The number of main effects that can be assessed in a 2 x 2 x 2 factorial experiment. • answer

25. Surprise--$300 • In a factorial experiment, this F-ratio, when significant, should be interpreted first. • answer

26. Surprise--$400 • In any ANOVA, these are added in order to obtain SSwithin treatment. • answer

27. Surprise--$500 • Use a within-subjects design when subjects are _____ to obtain and individual differences are ______. • answer

28. Compare & Contrast--$100 • A: What is 1 and more than 1? • Back to board

29. Compare & Contrast--$200 • A: What is the numerator or MSBetween Treatments? • Back to board

30. Compare & Contrast--$300 • A: What are P totals? • Back to board

31. Compare & Contrast--$400 • A: What is a between-subjects design? • Back to board

32. Compare & Contrast--$500 • A: What is MSWithin Treatment and MSerror? • Back to board

33. Repeated-M ANOVA--$100 • A: What is SS Between Subjects? • Back to board

34. Repeated-M ANOVA--$200 • A: What is SS Between Treatments? • Back to board

35. Repeated-M ANOVA--$300 • A: What is 4? • Back to board

36. Repeated-M ANOVA--$400 • A: What is SSerror and SSBetween Subjects? • Back to board

37. Repeated-M ANOVA--$500 • A: What is 36? • Back to board

38. Factorial Design--$100 • A: What is main effect of A? • Back to board

39. Factorial Design--$200 • A: What is an interaction? • Back to board

40. Factorial Design--$300 • A: What are dfAxB(numerator) & df Within Treatment (denominator)? • Back to board

41. Factorial Design--$400 • A: What are main effects? • Back to board

42. Factorial Design--$500 • A: What is simple main effects? • Back to board

43. Factorial ANOVA--$100 • A: What are 3? • Back to board

44. Factorial ANOVA--$200 • A: What is between treatments? • Back to board

45. Factorial ANOVA--$300 • A: What are column (or row) totals (or means)? • Back to board

46. Factorial ANOVA--$400 • A: What are 8? • Back to board

47. Factorial ANOVA--$500 • A: What are treatment means and converge or cross? • Back to board

48. Surprise--$100 • A: What is no interaction ? • Back to board

49. Surprise--$200 • A: What are 3? • Back to board

50. Surprise--$300 • A: What is FAxB? • Back to board