Name_____________________________ Ψ 420 Ainsworth Psy 420 – Midterm 1 Part 2 – In lab (50 points total) Your 420 professor decides that he wants to find out how much impact amount of study time has on the first midterm. He randomly assigns students to study for 10 hours, 8 hours, 6 hours, 4 hours and 2 hours; recording each student’s midterm grade. Results are shown below. 10 hours 8 hours 6 hours 4 hours 2 hours 83 57 24 20 21 67 67 43 37 17 88 69 30 36 31 97 68 55 47 2 74 73 32 36 25 89 67 46 24 29 93 72 43 34 28 65 48 31 20 26 66 60 19 30 21 86 59 40 30 27 Mean 80.80 64.00 36.30 31.40 22.70 SD 11.87 7.82 10.98 8.45 8.42 SPSS output for 420 midterm study UNIANOVA score BY stdytime /CONTRAST (stdytime)=special (1 -1 0 0 0 0 1 -1 0 0 0 0 1 -1 0 0 0 0 1 -1) /METHOD = SSTYPE(3) /INTERCEPT = INCLUDE /PRINT = ETASQ HOMOGENEITY /CRITERIA = ALPHA(.05) /DESIGN = stdytime . Between-Subjects Factors10 hours 78 hours 76 hours 74 hours 72 hours 712345STDYTIMEValue Label N Levene's Test of Equality of Error VariancesaDependent Variable: SCORE1.202 4 30 .331F df1 df2 Sig.Tests the null hypothesis that the error variance of thedependent variable is equal across groups.Design: Intercept+STDYTIMEa.Name_____________________________ Ψ 420 Ainsworth Tests of Between-Subjects EffectsDependent Variable: SCORE18752.686a4 4688.171 53.763 .000 .87884919.314 1 84919.314 973.845 .000 .97018752.686 4 4688.171 53.763 .000 .8782616.000 30 87.200106288.000 3521368.686 34SourceCorrected ModelInterceptSTDYTIMEErrorTotalCorrected TotalType III Sumof Squares df Mean Square F Sig.Partial EtaSquaredR Squared = .878 (Adjusted R Squared = .861)a. Custom Hypothesis Tests Contrast Results (K Matrix)16.857016.8574.991.0026.66327.05128.571028.5714.991.00018.37838.7655.57105.5714.991.273-4.62215.76511.571011.5714.991.0271.37821.765Contrast EstimateHypothesized ValueDifference (Estimate - Hypothesized)Std. ErrorSig.Lower BoundUpper Bound95% Confidence Intervalfor DifferenceContrast EstimateHypothesized ValueDifference (Estimate - Hypothesized)Std. ErrorSig.Lower BoundUpper Bound95% Confidence Intervalfor DifferenceContrast EstimateHypothesized ValueDifference (Estimate - Hypothesized)Std. ErrorSig.Lower BoundUpper Bound95% Confidence Intervalfor DifferenceContrast EstimateHypothesized ValueDifference (Estimate - Hypothesized)Std. ErrorSig.Lower BoundUpper Bound95% Confidence Intervalfor DifferenceSTDYTIME Special ContrastComp 1Comp 2Comp 3Comp 4SCOREDependentVariableName_____________________________ Ψ 420 Ainsworth Questions referring to the 420 Midterm Experiment 1. Do the five groups meet the homogeneity of variance assumption? How do you know? (2 points) Yes, Levene’s test 2. Does amount of study time affect midterm scores? How do you know? (2 points) Yes, because of the overall ANOVA 3. Are the comparisons orthogonal? Show how you came to your conclusion. (2 points) No, because when you cross multiply them the sums are not zero (they’re -1) 4. As a planned comparison, does studying for 4 hours improve your score when compared to only 2 hours? Explain your answer. (1 point) Yes, because Comp 4 is significant at .05. 5. Is 4 hours of study significantly different than 2 hours of study after a Tukey adjustment? Show your work. (3 points) They have calculated Tukey as a mean difference (because that’s all they have from the table above) and come to the conclusion that it is no longer significant. /87.24.10 12.1110S AT TMSd qn= = = I think that’s right, I don’t have the book and I looked up the value of q online. If they did it the other way and got the F-Tukey they should get most of the credit.Name_____________________________ Ψ 420 Ainsworth A researcher is interested in whether different stats courses offered at CSUN aversely affect quality of life for students enrolled. The researcher randomly selected 5 students from each of the following courses: Psy 420, Psy 524 and Psy 520. Results and layout for a regression analysis are listed below, scores are on a scale of 1 to 10 with 10 meaning better quality of life. y x1 x2 420 9 -1 -1 8 -1 -1 8 -1 -1 8 -1 -1 7 -1 -1 524 6 -1 1 7 -1 1 7 -1 1 8 -1 1 6 -1 1 520 3 2 0 3 2 0 3 2 0 2 2 0 3 2 0 Output for Stat Class Study Variables Entered/RemovedbX2, X1a. EnterModel1Variables EnteredVariablesRemoved MethodAll requested variables entered.a. Dependent Variable: Yb. Model Summary.964a.930 .918 .683Model1R R Square Adjusted R SquareStd. Error ofthe EstimatePredictors: (Constant), X2, X1a. ANOVAb74.133 2 37.067 79.429 .000a5.600 12 .46779.733 14RegressionResidualTotalModel1Sum of Squares df Mean Square F Sig.Predictors: (Constant), X2, X1a. Dependent Variable: Yb.Name_____________________________ Ψ 420 Ainsworth Coefficientsa5.867 .176 33.261 .000-1.533 .125 -.941 -12.294 .000-.600 .216 -.212 -2.777 .017(Constant)X1X2Model1B Std. ErrorUnstandardized CoefficientsBetaStandardizedCoefficientst Sig.Dependent Variable: Ya. Questions related to the Stat Course Study 6. Does quality of life differ for the three statistics courses? Explain. (2 points) Yes, regression above is significant. 7. What is the η2 value for the effect of statistics classes? (2 points) 274.133.9379.733η= = 8. What is the predicted score for the first subject in the 420 course? Show how you got the answer. (2 points) The answer is 8. And they could have got that answer by either solving for ' 1* ( 1.533) 1*( .60) 5.867Y= − − − − +or they could have said that it was 8 because that is the mean for group 1. 9. Is quality of life statistically worse for students in the 524 course when compared to the 420 course? How do you know? (2 points) Yes because the second b is significant and in the right direction. 10. How do you interpret the B for X1 (-1.533)? The constant (5.867)? (2 points) B is 1/3 the distance between the 2 groups (520 vs. 524 and 420) Or it’s the distance between 524 and 420 and the grand mean Or it’s half the distance between 520 and the grand mean.Name_____________________________ Ψ 420 Ainsworth 11. You are an experimenter trying to test the effect of different disorders (Aspergers, Pervasive Developmental Disorder, Autism) and different types of behavioral therapy (Floor time, Discrete Trials, Pivotal Response Training) on length of eye contact of each child (measured in