Week 8 PSY/CJ 315 Due 11/27/16 1. The following data summarize the results from an independent-measures study comparing three treatment conditions. I 2 3 8 6 5 6 M=5 T=30 SS=24 a. b. 2. Name: ________________________ Treatment II 5 9 10 13 8 9 M=9 T=54 SS=34 III 8 6 12 11 11 12 M=10 T=60 SS=30 N=18 G=144 X2=1324 Use an ANOVA with =.05 to determine whether there are any significant differences among the three treatment means. Calculate 2 to measure the effect size for this study. The following data summarize the results from an independent-measures study comparing three treatment conditions. Treatment I 4 2 5 1 3 7 4 4 8 2 M=4 T=40 SS=44 a. b. II 5 7 3 4 8 6 2 7 3 5 M=5 T=50 SS=36 III 5 7 6 6 8 9 6 4 6 8 M=6.5 T=65 SS=20.5 N=30 G=155 X2=933 Calculate the sample variances for each of the three samples. Use an ANOVA with =.05 to determine whether there are any significant differences among the three treatment means. 3. The following values are from an independent-measures study comparing three treatment conditions. I n=4 SS=8 a. b. 4. 5. Treatment II n=4 SS=10 III n=4 SS=18 Compute the variance for each sample. Compute MSwithin which would be the denominator of the F-ratio for an ANOVA. Because the samples are all the same size, you should find that MSwithin is equal to the average of the three sample variances. The following summary table presents the results from an ANOVA comparing three treatment conditions with n=6 participants in each condition. Complete all missing values. (Hint: Start with the df column.) Source SS Between Treatments Within Treatments88 Total _____ df _____ _____ _____ MS _____ F = 7.16 _____ _____ A psychologist would like to examine the effects of different testing methods on the final performance of college students. One group gets regular quizzes, one group gets three large exams, and the third group only gets a final exam. At the end of the course, the psychologist interviews each student to get a measure of the student's overall knowledge of the material. Quizzes Exams Final Only 4 1 0 6 4 2 G = 36 3 5 0 X2 = 164 7 2 2 T = 20 T = 12 T=4 SS = 10 SS = 10 SS = 4 a. b. c. d. Do these data indicate any significant differences among the three methods? Test with = .05. Compute 2, the percentage of variance explained by the group differences, for these data. Write a sentence demonstrating how a research report would present the results of the hypothesis test and the measure of effect size. Compute Tukey's HSD to determine exactly which methods are significantly different. 6. A published report of a repeated-measures research study includes the following description of the statistical analysis. \"The results show significant differences among the treatment conditions, F(2,20) = 5.00, p< .05.\" a. How many treatment conditions were compared in the study? b. How many individuals participated in the study? 7. A recent study examined how applicants with a facial blemish such as a scar or birthmark fared in job interviews (Madera & Hebl, 2011). The results indicate that interviewers recalled less information and gave lower ratings to applicants with a blemish. In a similar study, participants conducted computer-simulated interviews with a series of applicants including one with a facial scar and one with a facial birthmark. The following data represent the ratings given to each applicant. Applicant Participant A B C D E a. b. 8. Scar 1 3 0 0 1 M=1 T=5 SS=6 Birthmark 1 4 2 0 3 M=2 T=10 SS=10 No Blemish 4 8 7 6 5 M=6 T=30 SS=10 Person Totals P=6 P = 15 N = 15 P=9 G = 45 P=6 X2 = 231 P=9 Use a repeated-measures ANOVA with =.05 to determine whether there are significant mean differences among the three conditions. Write a sentence demonstrating how a research report would present the results of the hypothesis test and the measure of effect size. The following data were collected from a repeated-measures study Treatments Participant A B C D _________________________________________ 1 6 3 3 0 2 4 4 2 2 3 4 2 0 2 4 10 7 7 4 _________________________________________ T = 24 T = 16 T = 12 T = 8 SS = 24 SS = 14 SS = 26 SS = 8 a. X2 = 332 G = 60 If the experiment uses an independent-measures design, can the researcher b. 9. conclude that the treatments are significantly different? Test at the .05 level of significance. If the experiment is done with a repeated-measures design, should the researcher conclude that the treatments are significantly different? Set alpha at .05 again. A researcher conducts a repeated-measures study comparing three treatment conditions with a sample of n = 12 participants. The results are evaluated with a repeated-measures ANOVA and an incomplete summary table follows. Provide the missing values. (Hint: begin with values for df). Source Between treatments Within treatments Between subjects Error Total 10. SS _____ _____ _____ 44 106 df _____ _____ _____ _____ _____ MS 10 F = _____ _____ The following matrix presents the results from an independent-measures, two-factor study with a sample of n=6 participants in each treatment condition. Note that one treatment mean is missing. Factor B B1 B2 A1 M=5 Factor A A2 a. b. c. M=7 M=3 What value for the missing mean would result in no main effect for factor A? What value for the missing mean would result in no main effect for factor B? What value for the missing mean would result in no interaction? Extra Credit (+1) The following table summarizes the results of a two-factor ANOVA evaluating an independentmeasures experiment with 2 levels of factor A, 3 levels of factor B, and n = 8 participants in each treatment condition. Fill in all missing values in the table. (Hint: start with the df column.) Source Between Treatments Factor A Factor B A X B Interaction Within Treatments SS 124 _____ _____ 20 _____ df _____ _____ _____ _____ _____ MS _____ _____ _____ 4 FA = 10 FB = _____ FAxB= _____ Total _____ _____