advertisement

Chelsea Hutto PSYC 8000 Exam 2 50 points Due 3/13/2014 1. What is multicollinearity? (1 pt) a. When predictor variables have a linear relationship with the outcome variable b. When predictor variables correlate very highly with each other c. When predictor variables are correlated with variables not in the regression model d. When predictor variables are independent 2. Which of the following is not a reason why multicollinearity a problem in regression? (1 pt) a. It leads to unstable regression coefficients. b. It limits the size of R. c. It creates heteroscedasticity in the data. d. It makes it difficult to assess the importance of individual predictors. 3. A researcher just ran a regression analysis with core self-evaluation, self-esteem, and locus of control predicting academic achievement. She noticed that the variance inflation factor (VIF) for both core self-evaluation and self-esteem is 15.03. What are VIF values an indicator of? Should Helen be worried about a VIF value of 15.03? Why or why not? (2 pt) VIF indicates whether a predictor has a strong linear relationship with the other predictor(s). If the largest VIF is greater than 10 then there is a cause for concern, therefore a VIF value of 15.03 would be worrisome. 4. Recent research has shown that lecturers are among the most stressed workers. A researcher wanted to know exactly what it was about being a lecturer that created this stress and subsequent burnout. She recruited 75 lecturers and administered several questionnaires that measured: Burnout (high score = burnt out), Perceived Control (high score = low perceived control), Coping Ability (high score = low ability to cope with stress), Stress from Teaching (high score = teaching creates a lot of stress for the person), Stress from Research (high score = research creates a lot of stress for the person), and Stress from Providing Pastoral Care (high score = providing pastoral care creates a lot of stress for the person). The outcome of interest was burnout. How would you interpret the unstandardized beta value for ‘stress from teaching’? (1 pt) Chelsea Hutto Coefficientsa Model 1 2 3 (C onst ant) Perceiv ed Cont rol Coping Ability (C onst ant) Perceiv ed Cont rol Coping Ability Stres s f rom Teac hing (C onst ant) Perceiv ed Cont rol Coping Ability Stres s f rom Teac hing Stres s f rom prov iding past oral Care Standardi zed Unst andardized Coef f ic ien Coef f ic ients ts B Std. Error Bet a .548 1. 558 .619 .088 .496 .372 .054 .485 10.119 3. 476 .633 .084 .507 .516 .070 .673 -. 240 .079 -. 257 6. 166 3. 615 .675 .082 .541 .507 .067 .663 -. 360 .087 -. 387 .182 .065 .193 t .352 7. 002 6. 851 2. 911 7. 548 7. 383 -3.042 1. 706 8. 271 7. 595 -4.143 2. 775 Sig. .726 .000 .000 .005 .000 .000 .003 .093 .000 .000 .000 .007 Collinearity St at ist ics Tolerance VIF .683 .683 1. 465 1. 465 .681 .370 .430 1. 469 2. 703 2. 326 .658 .369 .322 .578 1. 520 2. 708 3. 104 1. 730 a. Dependent Variable: Burnout a. As stress from teaching increases by a unit, burnout decreases by 0.36 of a unit. Therefore, stress from teaching protects against burnout. b. People with burnout are 36% more likely to be stressed when they teach. c. As stress from teaching increases by a unit, burnout increases by 0.36 of a unit. d. As stress from teaching increases by 0.36 of a standard deviation, burnout also increases by 0.36 of a standard deviation. 5. Which of the following is an example of perfect mediation? (1 pt) a. The interaction of the predictor and the mediator significantly predicts the outcome, but the variables themselves do not. b. The relationship between the predictor and the outcome remains the same when the mediator is included in the model. c. The strength of the relationship between the predictor and the outcome is reduced by exactly half when the mediator is included in the model. d. The relationship between the predictor and the outcome is completely wiped out when the mediator is included in the model. 6. In your own words, describe what moderation is. Then, outline the steps necessary to conduct a moderated regression analysis. (4 pt) Moderation is when the outcome of two variables depends on that of a third variable. Basically stating, we cannot infer the relationship between the two variables is accurate based on a third variable and the role it may play in the relationship. 7. A busy social life has been found to increase happiness in participants who are experiencing low levels of stress, but decrease happiness in participants who are experiencing high levels of stress. What is this an example of? (1 pt)**** a. Mediation b. Moderation c. Neither moderation nor mediation d. Semi-partial correlation 8. What is the Sobel test used for? (1 pt) a. To assess the significance of the direct effect in mediation analysis b. To assess the significance of the direct effect in moderation analysis Chelsea Hutto c. To assess the significance of the indirect effect in mediation analysis d. To assess the significance of the interaction effect in moderation analysis. 9. Imagine it was found that worry explains the relationship between depression and sleep problems (i.e., depressed people tend to worry more than non-depressed people, leading them to experience more sleep problems). Which of the following is the indirect effect? (1 pt) a. The relationship between worry and sleep problems, controlling for depression b. The effect of sleep problems on depression through worry c. The relationship between depression and sleep problems, controlling for worry d. The effect of depression on sleep problems through worry 10. List and describe Baron and Kenny’s (1986) 4 steps for assessing mediation. (4 pt) a. Run a regression analysis to evaluate whether predictor is related to the outcome (c) b. Run regression analysis to evaluate whether predictor is related to mediator (a) c. Run regression analysis to evaluate whether mediator is related to outcome (b) when predictor is included in model d. Assess whether direct effect of predictor on outcome (c’) is reduced when mediator is included in model i. Compare c’ to c ii. Look at significance of indirect effect (a*b) 11. An experiment was done to look at whether different relaxation techniques could predict sleep quality better than nothing. A sample of 400 participants were randomly allocated to one of four groups: massage, hot bath, reading or nothing. For one month each participant received the same relaxation technique for 30 minutes before going to bed each night. A special device was attached to the participant’s wrist that recorded their quality of sleep, providing them with a score out of 100. The outcome was the average quality of sleep score over the course of the month. Which of the following tables displays the most appropriate coding scheme for analysing these data? (Note: Delete the other tables, leaving only the correct one) (1 pt) Nothing Reading Hot bath Massage Dummy Variable 1 Dummy Variable 2 0 0 0 1 0 0 1 0 Dummy Variable 3 0 1 0 0 12. A simple slopes analysis: (1 pt) a. Is the slope of the regression line between a predictor and outcome variable. b. Looks at the relationship between a predictor and outcome variable at low, mean and high levels of a moderator. c. Compares regression slopes within different participants. Chelsea Hutto d. Quantifies the rate of decrease, or ‘slope’, of the direct effect when a mediator is present. 13. What is grand-mean centering? When conducting a moderated regression analysis, which variables need to be centered? Why is centering important for moderated regression? (3 pt) Centering refers to the process of transforming a variable into deviations around a fixed point, in grand mean centering this value is the grand mean. Predictor variables need to be centered, unless they are categorical. Outcome variables should not be centered. Centering is important for moderated regression because it makes interpretation of coefficients easier. For example, with centering, interaction is how much a predictor changes with one unit increase in the moderator when the predictor is equal to the mean. 14. A mediation analysis was conducted to look at whether coping ability mediated the relationship between perceived control and stress from pastoral care. Here is the output for that analysis: Chelsea Hutto The Sobel test statistic was 4.18, p < .001. Give the value of each of the following regression coefficients: c, a, b, and c’. Did coping ability mediate the relationship between perceived control and stress from pastoral care? How do you know? If there was a mediated relationship, was it complete mediation or partial mediation? (5 pt) a = (b = .286, p < .001) b = (b = .331, p < .001) c = (b = .071, p = .176) c’ = (b = -.024, p = .634) We are able to determine coping does mediate the relationship between stress and control by examining the c’ prime value (b = -.024, p = .634) as compared to the c value (b = .071, p = .176), as displayed, the strength of the relationship between control and stress is less when coping is included than when it isn’t included. Based off the results from the Sobel test (S = 4.18, p < .001) the indirect effect is significantly different from zero. This significant value also means that the predictor significantly affects the outcome variable via the mediator. 15. A moderated regression analysis was conducted to evaluate whether burnout (0=not burnt out, 1=burnt out) moderates the relationship between coping ability and stress from pastoral care. Here is the output: Interpret this output. Are coping ability and burnout predictors of stress from pastoral care? Does the relationship between coping ability and stress from pastoral care depend on whether someone is burnt out or not? (2 pt) Based on the beta value (b =.21, p = .03) coping ability and burnout are predictors of stress from pastoral care. Despite these results, the relationship between coping ablity and stress from pastoral care does not depend on whether someone is burnt out or not. Additionally, coping alone accounts for more stress (b = .25, p < .001) than coping and burnout combined (b = .21, p = .03). Chelsea Hutto 16. A researcher was interested in the effects of emotion-evoking music on exam performance. Before their SPSS exam, a lecturer took one group of students to a room in which calming music was being played. A different group of students were taken to another room in which the ‘death march’ was being played. The students then did the exam and their marks were noted. The SPSS output is below. The experimenter made no predictions about which form of support would produce the best exam performance. What should he report? (1 pt) Group Statistics Emotional Support SPSS Exam Mark Positive Support Negative Support N 20 20 Std. Deviation 5.0396 15.2129 Mean 65.1500 57.8000 Std. Error Mean 1.1269 3.4017 Independent Samples Test Levene's Test for Equality of Variances F SPSS Exam Mark Equal variances assumed Equal variances not assumed 18.117 Sig. .000 t-test for Equality of Means t Sig. (2-tailed) df Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper 2.051 38 .047 7.3500 3.5835 9.559E-02 14.6044 2.051 23.121 .052 7.3500 3.5835 -6.09E-02 14.7609 a. Students receiving positive music before the exam did significantly better than those receiving negative music, t(38) = 2.05, p = .047. b. Marks for students receiving positive music before the exam did not significantly differ from students receiving negative music, t(38) = 2.05, p = .047. c. Marks for students receiving positive music before the exam did not significantly differ from students receiving negative music, t(23.12) = 2.05, p = .052. d. Students receiving positive music before the exam did significantly better than those receiving negative music, t(23.12) = 2.05, p < .05, one-tailed. 17. An independent t-test is used to test for: (1 pt) a. Differences between means of groups containing the same entities when the sampling distribution is not normally distributed and the data do not have unequal variances. b. Differences between means of groups containing the same entities when the data are normally distributed have equal variances and data are at least interval. c. Differences between means of groups containing different entities when the data are not normally distributed or have unequal variances. d. Differences between means of groups containing different entities when the sampling distribution is normal, the groups have equal variances and data are at least interval. Chelsea Hutto 18. An paired-samples t-test is used to test for: (1 pt) a. Differences between means of groups containing different entities when the sampling distribution is normally distributed, and the data have equal variances and are at least ordinal. b. Differences between means of groups containing the same entities when the sampling distribution is normally distributed, and the data have equal variances and are at least interval. c. Differences between means of groups containing different entities when the sampling distribution is not normally distributed. d. Differences between means of groups containing the same entities when the sampling distribution is not normally distributed and the data do not have unequal variances. 19. If you use a paired samples t-test: (1 pt)**** a. There ought to be less unsystematic variance compared to the independent t-test. b. The same participants take part in both experimental conditions. c. Other things being equal, you do not need as many participants as you would for an independent samples design. d. All of these are correct. 20. A small standard error of differences tells us: (1 pt) a. That sample means can deviate quite a lot from the population mean and so differences between pairs of samples can be quite large by chance alone. b. That most pairs of samples from a population will have very similar means. c. That the differences between scores are not normally distributed. d. That the differences between scores are normally distributed. 21. A researcher wanted to evaluate whether professors experienced higher levels of stress from teaching or from research. The researcher had professors report their levels of stress from research and from teaching. The results are below. Was there a significant difference between stress from research and stress from teaching? How do you know? Which type of stress did professors report more of? (2 pt) Chelsea Hutto Yes there is a significant difference between stress from research and stress from teaching as displayed by the t value (t = -6.60, p < .001). Additionally, professors reported higher levels of stress from research as compared to stress from teaching. 22. A psychologist was looking at the effects of an intervention on depression levels. Three groups were used: waiting list control, treatment and post-treatment (a group who had had the treatment 6 months before). Based on the output for these tests, what should the researcher conclude? (1 pt) Multi ple C omparisons Dependent Variable: BDIDI F Bonf erroni (I ) Group treatment Post Treatment Control Games-Howell treatment Post Treatment Control (J ) Group Post Treatment Control treatment Control treatment Post Treatment Post Treatment Control treatment Control treatment Post Treatment Mean Dif f erence (I -J) Std. Error -2.4421 2. 54468 -7.9413* 2. 54468 2. 4421 2. 54468 -5.4992 2. 54468 7. 9413* 2. 54468 5. 4992 2. 54468 -2.4421 2. 48536 -7.9413* 2. 95195 2. 4421 2. 48536 -5.4992* 2. 12958 7. 9413* 2. 95195 5. 4992* 2. 12958 Sig. 1. 000 .009 1. 000 .108 .009 .108 .596 .031 .596 .043 .031 .043 95% C onf idenc e I nterv al Lower Bound Upper Bound -8.7702 3. 8859 -14.2694 -1.6133 -3.8859 8. 7702 -11.8272 .8289 1. 6133 14. 2694 -. 8289 11. 8272 -8.7162 3. 8319 -15.2320 -. 6506 -3.8319 8. 7162 -10.8347 -. 1636 .6506 15. 2320 .1636 10. 8347 *. The mean dif f erenc e is signif icant at t he . 05 lev el. a. The post hoc tests are inconclusive. b. The treatment group was significantly different from the control group but not the post-treatment group, and the post-treatment group was not significantly different from the control group. c. The treatment group was significantly different from the control group but not the post-treatment group, and the post-treatment group was significantly different from the control group. d. The treatment group was significantly different from the post-treatment and control group, and the post-treatment group was significantly different from the control group. 23. Imagine you compare the effectiveness of four different types of stimulant to keep you awake while studying statistics using a one-way ANOVA. The null hypothesis would be that all four treatments have the same effect on the mean time kept awake. How would you interpret the alternative hypothesis? (1 pt) a. Two of the four stimulants have the same effect on the mean time spent awake. b. At least two of the stimulants will have different effects on the mean time spent awake. c. All four stimulants have different effects on the mean time spent awake. d. None of the above Chelsea Hutto 24. The table below contains the length of time (minutes) for which different groups of students were able to stay awake to study statistics after consuming 500 ml of one of three different types of stimulants. What is the variation in scores from groups A to B to C known as? (1 pt) A B C 20 15 40 15 12 33 120 7 50 57 18 135 a. b. c. d. The within-groups variance Homogeneity of variance The grand variance The between-groups variance 25. When the between-groups variance is a lot larger than the within-groups variance, the Fvalue is ____ and the likelihood of such a result occurring because of sampling error is _____ (1 pt) a. small; low b. large; low c. large; high d. small; high 26. Why isn’t it acceptable to just use a series of t-tests, rather than using an ANOVA, to compare means across 3 or more groups? (1 pt) T tests are just a linear model with one binary predictor variable, whereas an ANOVA allows us to compare means on a single DV across more than two groups. Additionally, by doing multiple t tests on data, the Type 1 error rate is inflated beyond acceptable levels, but if an ANOVA is conducted instead, this controls for the likelihood of Type 1 error. 27. In an ANOVA, if the differences between group means are large enough, then: a. The resulting model will be a better fit of the data than the grand mean. b. The resulting model will be a poorer fit of the data than the grand mean. c. It is likely that the assumption of sphericity will have been violated. d. The assumption of homogeneity of variances is likely to have been violated. 28. A researcher wanted to look at whether individuals with tattoos and/or piercings differ in their level of alcohol consumption. Here are the results: Chelsea Hutto Was there a significant difference between the groups in terms of their alcohol consumption? How do you know? If there was a difference, which groups were significantly different from one another? (3 pt) Based off the mean difference values and the corresponding p values, there are significant differences between groups in terms of alcohol consumption. Specifically, no tattoo, no piercing differed significantly from piercings only in addition to tattoos and piercings condition. Tattoos only also differed significantly from piercings only and tattoos and piercings. 29. After an ANOVA you need more analysis to find out which groups differ. When you did not generate specific hypotheses before the experiment use: (1 pt) a. Planned contrasts b. t-tests c. Post hoc tests d. Bootstrapping 30. A study was conducted to look at whether caffeine improves productivity at work in different conditions. There were two independent variables. The first independent variable was email, which had two levels: ‘email access’ and ‘no email access’. The second independent variable was caffeine, which also had two levels: ‘caffeinated drink’ and ‘decaffeinated drink’. Different participants took part in each condition. Productivity was recorded at the end of the day on a scale of 0 (I may as well have stayed in bed) to 20 (wow! I got enough work done today to last all year). Looking at the group means in the table below, which of the following statements best describes the data?(1 pt) Chelsea Hutto Decaffeinated Drink Caffeinated Drink No Email 12.08 19.83 Email 5.49 11.98 a. A significant interaction effect is likely to be present between caffeine consumption and email access. b. There is likely to be a significant main effect of caffeine. c. The effect of email is relatively unaffected by whether the drink was caffeinated. d. The effect of caffeine is about the same regardless of whether the person had email access. 31. What type of ANOVA is used when there are two independent variables each with more than two levels, and with different participants taking part in each condition? (1 pt) a. One-way independent b. One-way between subjects c. Mixed d. Factorial 32. An experiment was done to look at whether there is an effect of the number of hours spent practicing a musical instrument and gender on the level of musical ability. A sample of 30 (15 men and 15 women) participants who had never learnt to play a musical instrument before were recruited. Participants were randomly allocated to one of three groups that varied in the number of hours they would spend practising every day for 1 year (0 hours, 1 hours, 2 hours). Men and women were divided equally across groups. All participants had a one-hour lesson each week over the course of the year, after which their level of musical skill was measured on a 10-point scale ranging from 0 to 10. An ANOVA was conducted on the data from the experiment. Looking at the output below, which of the following sentences is correct? (1 pt) a. There was a significant main effect of practice. This means that men and women significantly differed in the amount of practice that they did. b. There was a significant main effect of gender. Looking at the group means, we can see that women achieved a significantly higher level of musical skill (M = 5.53) than males (M = 4.87). Chelsea Hutto c. There was no significant practice gender interaction effect, indicating that if we ignore the gender of the participant, the number of hours spent practicing did not significantly affect the level of musical skill. d. There was no significant main effect of gender. This means that overall, when we ignore the number of hours spent practicing, the gender of the participant did not have a significant effect on the level of musical skill. 33. In a replication of the above experiment, slightly different results were obtained, and the following graph illustrates these new findings. Which of the following sentences best describes the pattern of results shown in the graph? (1 pt) a. The graph shows that the relationship between musical skill and time spent practicing was the same for men and women. b. The graph shows that the relationship between musical skill and time spent practicing was different for men and women. c. The graph indicates that men and women were most musically skilled when they practiced for 2 hours per day. d. None of the above