230 Jeopardy Unit 4

1. 230 Jeopardy Unit 4 Repeated-Measures ANOVA Chi-Square Factorial Design Factorial ANOVA Correlation $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

2. Chi-Square--$100 • Data must be measured on this type of scale in order to use the Chi-Square statistic. • . • answer

3. Chi-Square--$200 • The proportions specified by the null hypothesis are used to compute these. • answer

4. Chi-Square--$300 • If an individual in the sample is counted in more than one category, then this assumption is violated. • answer

5. Chi-Square--$400 • Use this test to determine whether consumers have a preference among four leading brands of toothpaste. • answer

6. Chi-Square--$500 • The measure of effect size used for a 2 x 2 matrix and a matrix larger than 2 x 2, respectively. • answer

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

8. 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

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

10. 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

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

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

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

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

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

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

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

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

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

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

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

22. Correlation--$100 • When two variables tend to move in the same direction • answer

23. Correlation--$200 • A perfect correlation is indicated by a correlation coefficient of • answer

24. Correlation--$300 • On a scatterplot, a negative correlation looks like this • answer

25. Correlation--$400 • Compute this to determine whether a consistent relationship exists between two rank-order measures. • answer

26. Correlation--$500 • Conceptually, the Pearson correlation coefficient is computed by dividing _________ by _________. • answer

27. Chi-Square--$100 • A: What is nominal? • Back to board

28. Chi-Square--$200 • A: What are expected frequencies? • Back to board

29. Chi-Square--$300 • A: What is the assumption of independence? • Back to board

30. Chi-Square--$400 • A: What is goodness of fit? • Back to board

31. Chi-Square--$500 • A: What is goodness of fit? • Back to board

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

47. Correlation--$100 • A: What is a positive correlation? • Back to board

48. Correlation--$200 • A: What is 1 (positive & negative)? • Back to board

49. Correlation--$300 • A: What is an envelope moving down from left to right? • Back to board

50. Correlation--$400 • A: What is the Spearman correlation? • Back to board