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Stats/Methods II JEOPARDY. Jeopardy Compare & Contrast Repeated- Measures ANOVA Factorial Design Factorial ANOVA Surprise $100 $200$200 $300 $500 $400.

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Presentation on theme: "Stats/Methods II JEOPARDY. Jeopardy Compare & Contrast Repeated- Measures ANOVA Factorial Design Factorial ANOVA Surprise $100 $200$200 $300 $500 $400."— Presentation transcript:

1 Stats/Methods II JEOPARDY

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

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 df Total = 40, then df Within Treatments = ___. answer

13 Factorial Design--$100 μ A1 = μ A2 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 F AxB. 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 SS within 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 MS Between 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 MS Within Treatment and MS error ? 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 SS error and SS Between 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 df AxB (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 F AxB ? Back to board

51 Surprise--$400 A: What are SS inside each treatment? Back to board

52 Surprise--$500 A: What are difficult and large? Back to board


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