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230 Jeopardy Unit 4

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.

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230 Jeopardy Unit 4

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  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

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