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PSYCHOLOGY 291 EXAM 4 STUDY GUIDE Exam 4 RDSA study guide Chapter 8 Study Guide 1. A study finds a correlation coefficient of r = .52. According to Cohen’s benchmarks, the magnitude of this ... effect is: a. modest. b. large. c. multiply determined. d. categorical. 2. Which of the following graph formats is the best way to examine an association claim between a categorical variable and a quantitative variable? a. A scatterplot b. A line graph c. A bar graph d. A pie chart 3. When examining an association claim using a bar graph, an association is indicated by which of the following? a. A difference in the height between the bars b. The number of bars in the graph c. The number of observations that make each bar d. The direction of the bars 4. When examining an association in which one variable is categorical and one is quantitative, which of the following is NOT likely to be used? a. A t test b. A correlation c. A scatterplot d. A bar graph 5. While reading about a research study, which of the following would tell you that an association claim is being made? a. The presence of a scatterplot or bar graph b. The measurement of two variables c. The use of a correlation coefficient d. The interrogation of internal validity 6. RESEARCH STUDY 8.1: Dr. Guidry conducts a study examining the relationship between the number of friends one has and the experience of daily stress and life satisfaction. She randomly samples 1,500 elderly men and women in Nashville, Tennessee (the state capital), located in the southern United States. Below are her findings. • Life satisfaction and experience of daily stress: r = .57 (p = .01) • Number of friends one has and experience of daily stress: r = .09, not sig. • Number of friends one has and life satisfaction: r = .36 (p = .04) In evaluating Dr. Guidry’s study, you question the construct validity of the study. Which of the following questions would you be asking? a. How did Dr. Guidry recruit her participants? b. Which statistic did Dr. Guidry compute? c. How reliable is the measure of daily stress? d. Does the number of friends cause people to experience less stress? 7. RESEARCH STUDY 8.1: Dr. Guidry conducts a study examining the relationship between the number of friends one has and the experience of daily stress and life satisfaction. She randomly samples 1,500 elderly men and women in Nashville, Tennessee (the state capital), located in the southern United States. Below are her findings. • Life satisfaction and experience of daily stress: r = .57 (p = .01) • Number of friends one has and experience of daily stress: r = .09, not sig. • Number of friends one has and life satisfaction: r = .36 (p = .04) According to the benchmarks established by Cohen, what type of effect size has Dr. Guidry found for the association between number of friends and life satisfaction? a. Very small b. Small c. Medium d. Large 8. RESEARCH STUDY 8.1: Dr. Guidry conducts a study examining the relationship between the number of friends one has and the experience of daily stress and life satisfaction. She randomly samples 1,500 elderly men and women in Nashville, Tennessee (the state capital), located in the southern United States. Below are her findings. • Life satisfaction and experience of daily stress: r = .57 (p = .01) • Number of friends one has and experience of daily stress: r = .09, not sig. • Number of friends one has and life satisfaction: r = .36 (p = .04) Comparing all three correlations, Dr. Guidry will be most able to accurately predict life satisfaction from the experience of daily stress because the relationship: a. is negative. b. has the largest effect size. c. was reported first. d. was statistically significant. 9. RESEARCH STUDY 8.1: Dr. Guidry conducts a study examining the relationship between the number of friends one has and the experience of daily stress and life satisfaction. She randomly samples 1,500 elderly men and women in Nashville, Tennessee (the state capital), located in the southern United States. Below are her findings. • Life satisfaction and experience of daily stress: r = .57 (p = .01) • Number of friends one has and experience of daily stress: r = .09, not sig. • Number of friends one has and life satisfaction: r = .36 (p = .04) Which of the following conclusions can Dr. Guidry draw about the number of friends one has and life satisfaction based on her statistical analyses? a. The probability of her sample coming from a zero association population is about 4%. b. The probability of her sample coming from a zero association population is about 96%. c. The relationship is not statistically significant. d. The strong correlation means that the number of friends one has causes an increase in life satisfaction. 10. RESEARCH STUDY 8.1: Dr. Guidry conducts a study examining the relationship between the number of friends one has and the experience of daily stress and life satisfaction. She randomly samples 1,500 elderly men and women in Nashville, Tennessee (the state capital), located in the southern United States. Below are her findings. • Life satisfaction and experience of daily stress: r = .57 (p = .01) • Number of friends one has and experience of daily stress: r = .09, not sig. • Number of friends one has and life satisfaction: r = .36 (p = .04) The “not sig.” in Dr. Guidry’s findings indicates all of the following EXCEPT: a. It is likely that the association between number of friends one has and experience of daily stress is from a zero association population. b. Effect size could not be calculated. c. There is not a statistically significant association between the two variables. d. She cannot reliably predict a study participant’s experience of daily stress from the participant’s number of friends. 11. RESEARCH STUDY 8.1: Dr. Guidry conducts a study examining the relationship between the number of friends one has and the experience of daily stress and life satisfaction. She randomly samples 1,500 elderly men and women in Nashville, Tennessee (the state capital), located in the southern United States. Below are her findings. • Life satisfaction and experience of daily stress: r = .57 (p = .01) • Number of friends one has and experience of daily stress: r = .09, not sig. • Number of friends one has and life satisfaction: r = .36 (p = .04) In determining whether the relationship between two of Dr. Guidry’s variables was statistically significant, which of the following must be considered? a. Sample size and number of variables analyzed b. Direction of the association and strength of the association c. Sample size and effect size d. The number of outliers and the direction of the association 12. RESEARCH STUDY 8.1: Dr. Guidry conducts a study examining the relationship between the number of friends one has and the experience of daily stress and life satisfaction. She randomly samples 1,500 elderly men and women in Nashville, Tennessee (the state capital), located in the southern United States. Below are her findings. • Life satisfaction and experience of daily stress: r = .57 (p = .01) • Number of friends one has and experience of daily stress: r = .09, not sig. • Number of friends one has and life satisfaction: r = .36 (p = .04) Dr. Guidry realizes that the women in her study have more friends than the men in her study. This might result in which of the following? a. Outliers due to subgroups b. Larger effect sizes c. More measured variables d. Spurious associations due to subgroups 13. RESEARCH STUDY 8.1: Dr. Guidry conducts a study examining the relationship between the number of friends one has and the experience of daily stress and life satisfaction. She randomly samples 1,500 elderly men and women in Nashville, Tennessee (the state capital), located in the southern United States. Below are her findings. • Life satisfaction and experience of daily stress: r = .57 (p = .01) • Number of friends one has and experience of daily stress: r = .09, not sig. • Number of friends one has and life satisfaction: r = .36 (p = .04) Dr. Guidry creates a scatterplot of the relationship between the experience of daily stress and life satisfaction. In doing so, she realizes there are three scores that seem to be very extreme and are nowhere near the other points on the scatterplot. Specifically, it appears that three people report very high levels of daily stress and very low levels of life satisfaction. Dr. Guidry should probably consider these scores _________. a. random b. moderators c. outliers d. curvilinear scores 14. RESEARCH STUDY 8.1: Dr. Guidry conducts a study examining the relationship between the number of friends one has and the experience of daily stress and life satisfaction. She randomly samples 1,500 elderly men and women in Nashville, Tennessee (the state capital), located in the southern United States. Below are her findings. • Life satisfaction and experience of daily stress: r = .57 (p = .01) • Number of friends one has and experience of daily stress: r = .09, not sig. • Number of friends one has and life satisfaction: r = .36 (p = .04) Dr. Guidry creates a scatterplot of the relationship between the experience of daily stress and life satisfaction. In doing so, she realizes there are three scores that seem to be very extreme and are nowhere near the other points on the scatterplot. Specifically, it appears that three people report very high levels of daily stress and very low levels of life satisfaction. Which of the following statements is NOT true? a. These scores may have strengthened the correlation between these two variables. b. These scores are more likely to have an effect because of the large sample size. c. These scores are more likely to have an effect because they are extreme on both variables. d. These scores may be considered outliers. 15. RESEARCH STUDY 8.1: Dr. Guidry conducts a study examining the relationship between the number of friends one has and the experience of daily stress and life satisfaction. She randomly samples 1,500 elderly men and women in Nashville, Tennessee (the state capital), located in the southern United States. Below are her findings. • Life satisfaction and experience of daily stress: r = .57 (p = .01) • Number of friends one has and experience of daily stress: r = .09, not sig. • Number of friends one has and life satisfaction: r = .36 (p = .04) Dr. Guidry has decided to examine one of her relationships with a scatterplot to double-check for a curvilinear relationship. Which relationship will be most important for her to examine? a. Life satisfaction and experience of daily stress b. Number of friends one has and experience of daily stress c. Number of friends one has and life satisfaction d. Life satisfaction, experiences of daily stress, and number of friends one has simultaneously 16. RESEARCH STUDY 8.1: Dr. Guidry conducts a study examining the relationship between the number of friends one has and the experience of daily stress and life satisfaction. She randomly samples 1,500 elderly men and women in Nashville, Tennessee (the state capital), located in the southern United States. Below are her findings. • Life satisfaction and experience of daily stress: r = .57 (p = .01) • Number of friends one has and experience of daily stress: r = .09, not sig. • Number of friends one has and life satisfaction: r = .36 (p = .04) Matt, Dr. Guidry’s research assistant, is discussing the findings of the study with some other students. He claims that the experience of more daily stress causes people to have lower life satisfaction. Which of the following causal criteria did Matt meet? a. The covariance of cause and effect b. Temporal precedence c. Internal validity d. External validity 17. RESEARCH STUDY 8.1: Dr. Guidry conducts a study examining the relationship between the number of friends one has and the experience of daily stress and life satisfaction. She randomly samples 1,500 elderly men and women in Nashville, Tennessee (the state capital), located in the southern United States. Below are her findings. • Life satisfaction and experience of daily stress: r = .57 (p = .01) • Number of friends one has and experience of daily stress: r = .09, not sig. • Number of friends one has and life satisfaction: r = .36 (p = .04) Dr. Guidry submits her study for publication in a scientific journal. If one of the peer reviewers is concerned about the external validity of her study, which of the following is the most important aspect of Dr. Guidry’s study to consider? a. The random sampling technique used to recruit the participants b. The number of people in the sample c. The use of three measured variables d. The number of significant findings 18. RESEARCH STUDY 8.1: Dr. Guidry conducts a study examining the relationship between the number of friends one has and the experience of daily stress and life satisfaction. She randomly samples 1,500 elderly men and women in Nashville, Tennessee (the state capital), located in the southern United States. Below are her findings. • Life satisfaction and experience of daily stress: r = .57 (p = .01) • Number of friends one has and experience of daily stress: r = .09, not sig. • Number of friends one has and life satisfaction: r = .36 (p = .04) Considering Dr. Guidry’s study, her results could most safely be generalized to which of the following groups? a. People in the southern United States b. Elderly people c. People with a high number of friends d. People with high life satisfaction 19. RESEARCH STUDY 8.1: Dr. Guidry conducts a study examining the relationship between the number of friends one has and the experience of daily stress and life satisfaction. She randomly samples 1,500 elderly men and women in Nashville, Tennessee (the state capital), located in the southern United States. Below are her findings. • Life satisfaction and experience of daily stress: r = .57 (p = .01) • Number of friends one has and experience of daily stress: r = .09, not sig. • Number of friends one has and life satisfaction: r = .36 (p = .04) Considering Dr. Guidry’s sample, which of the following statements is true? a. The association found in her study could probably generalize to young adults. b. The association found in her study could probably generalize to elderly people in other large cities in the South. c. The association found in her study could probably generalize to people living in other capital cities (e.g., Sacramento, California). d. The association found in her study could probably generalize to elderly persons living in nursing homes. 20. RESEARCH STUDY 8.1: Dr. Guidry conducts a study examining the relationship between the number of friends one has and the experience of daily stress and life satisfaction. She randomly samples 1,500 elderly men and women in Nashville, Tennessee (the state capital), located in the southern United States. Below are her findings. • Life satisfaction and experience of daily stress: r = .57 (p = .01) • Number of friends one has and experience of daily stress: r = .09, not sig. • Number of friends one has and life satisfaction: r = .36 (p = .04) Dr. Guidry finds that the relationship between the number of friends one has and life satisfaction is stronger for men than for women. In this study, sex (male or female) is considered a(n): a. outlier. b. cause. c. moderator. d. spurious variable. 21. RESEARCH STUDY 8.1: Dr. Guidry conducts a study examining the relationship between the number of friends one has and the experience of daily stress and life satisfaction. She randomly samples 1,500 elderly men and women in Nashville, Tennessee (the state capital), located in the southern United States. Below are her findings. • Life satisfaction and experience of daily stress: r = .57 (p = .01) • Number of friends one has and experience of daily stress: r = .09, not sig. • Number of friends one has and life satisfaction: r = .36 (p = .04) Dr. Guidry finds that the relationship between the number of friends one has and life satisfaction is stronger for men than for women. Why might Dr. Guidry have looked for this difference? a. To examine her study’s external validity b. To examine her study’s internal validity c. To determine whether the association was curvilinear d. To determine whether the association was spurious 22. Which of the following is true of statistical significance testing? a. It is necessary for establishing internal validity. b. It can lead to an incorrect conclusion about the population. c. It involves testing effect sizes. d. It is only done when you have two quantitative variables. 23. Which of the following is NOT true of finding a stronger effect size in an association claim? a. There will be a greater likelihood of finding a statistically significant relationship. b. There will be greater accuracy in predicting one variable as opposed to another. c. There will be greater likelihood of a finding being important in the real world. d. There will be greater construct validity. 24. In which of the following cases might a small effect still be important? a. When the sample is very large b. When the study has life-or-death implications c. When the finding is also statistically significant d. When external validity is high 25. Which of the following is true of the relationship between effect size and statistical significance? a. Larger effect sizes are advantageous for statistical significance. b. Statistical significance alone is sufficient to indicate effect size. c. An association’s effect size has no effect on statistical significance. d. Effect size and statistical significance are synonymous terms. 26. Statistical significance depends on which of the following? a. Sample size and number of variables analyzed b. Direction of the association and strength of the association c. Sample size and effect size d. Number of outliers and direction of the association 27. Martin has found a correlation of r = .18 between the two variables of using prescription stimulants (e.g., Adderall) and frontal lobe activity. This correlation is more likely to be statistically significant if: a. the study can be applied to the real world. b. Martin used a larger number of subjects. c. Martin measured frontal lobe activity extremely accurately. d. Martin’s measure of prescription stimulant use is categorical. 28. All of the following are true of outliers EXCEPT: a. They have the biggest effect when dealing with large sample sizes. b. They can affect the direction of an association. c. They can affect the strength of an association. d. They are especially problematic when there are outliers on both variables. 29. Why are curvilinear relationships hard to detect with correlation coefficients (r)? a. Curvilinear relationships require a large amount of scores. b. r always looks for the best straight line to fit the data. c. r always assumes a zero association. d. r always assumes a negative relationship. 30. Which of the following questions is NOT necessary to ask when interrogating statistical validity? a. What is the effect size? b. Are there subgroups? c. Is random assignment affecting the findings? d. Could outliers be affecting the relationship? 31. For a third variable to be plausible as the explanation in an established association, which of the following must also be true? a. The third variable must be related to both of the measured variables in the original association. b. The third variable must be measured on the same scale as the original measured variables. c. The third variable must be a categorical variable. d. The third variable must have a positive relationship with the two measured variables in the original association. 32. When evaluating the external validity of an association claim, which of the following is the most important issue to consider? a. The way the sample was selected from the population b. The size of the sample c. The number of subgroups d. The size of the original population 33. If an association study did not select people for the study by using random sampling, which of the following statements is true? a. The association should be rejected as inconclusive. b. The study must be done again using the same participants. c. The effect size should be considered, but tests of statistical significance should not. d. The findings should be replicated in another population. 34. Which of the following is true of moderators? a. They help establish a cause and effect relationship. b. They decrease effect size. c. They can inform external validity. d. They weaken statistical significance. 35. What is the relationship between moderators and external validity? a. Moderators suggest that associations may be spurious. b. Moderators suggest that associations may not generalize to all subgroups of people. c. Moderators are necessary for external validity to be established. d. Moderators suggest that an association between two variables will extend to another variable. 36. A study finds a correlation coefficient of r = .52. This number gives you information about which of the following? a. Statistical significance and effect size b. Strength and direction of the relationship c. Statistical validity and external validity d. Type of relationship and importance 37. Which of the following means a study used a bivariate correlational design? a. The presence of measured variables b. The use of correlational statistics c. The inclusion of quantitative variables d. The depiction of a bar graph 38. A study finds a correlation coefficient of r = .52 and reports p < .05. The p is a _________. a. population value b. possibility assessment c. probability estimate d. plausible significance approximation 39. A study finds a correlation coefficient of r = .52 and reports p < .05. The p value indicates which of the following? a. The correlation is negative. b. The correlation is unlikely to have come from a zero association population. c. The correlation is not statistically significant. d. The effect size is large. 40. If there is not a full range of scores on one of the variables, this is known as _________. a. spurious data b. an outlier effect c. restriction of range d. null effect 41. The figure above is an example of a _________. a. bar graph b. line graph c. data plot d. scatterplot 42. Imagine you calculated the correlation coefficient for the data presented in the figure, and the resulting number was r = –.44. Looking at the figure, how would you know the number you calculated is incorrect? a. There aren’t 44 dots in the figure. b. Correlation coefficients cannot be smaller than 1. c. The figure shows a positive relationship between optimism and life satisfaction. d. There wouldn’t be a way to know this. 43. Which of the following could you conclude by looking at the figure? a. There is a causal relationship between optimism and life satisfaction. b. As optimism increases, life satisfaction also increases. c. The relationship between optimism and life satisfaction is negative. d. More people reported being optimistic than being satisfied with life. 44. The figure above is an example of ___________________. a. bar graph b. line graph c. data plot d. scatterplot 45. In order to create the figure, which of the following pieces of information would you need? a. The mean optimism scores of people who voted and people who did not vote b. The correlation coefficient between voting behavior and optimism c. The number of people who voted and did not vote in 2016 d. Each individual participant’s optimism score 46. Which of the following can you conclude by looking at the figure above? a. The number of people who voted in 2016 is larger than the number of people who did not vote in 2016. b. There is an association between voting behavior in 2016 and one’s level of optimism. c. Voting in 2016 caused increases in one’s level of optimism. d. Optimistic people will be more likely to vote in 2018. 47. When interrogating the construct validity of an association claim, which of the following statements is true? a. Quantitative variables need to be assessed, but qualitative variables do not. b. The reliability of the measures is more important than their validity. c. How each variable was measured must be considered. d. Only the construct validity of the outcome variable needs to be interrogated. 48. If a person is asking whether the variables in an association claim are measured appropriately, _________ is being interrogated. a. construct validity b. external validity c. internal validity d. statistical validity 49. The temporal precedence criterion is also known as the _________ problem. a. third variable b. covariance c. association d. directionality 50. Bivariate association claims’ failure to meet the criteria of temporal precedence and internal validity means that _________ cannot be_________. a. covariance; established b. construct validity; interrogated c. hypotheses; tested d. causal inferences; made -------- 1. Which of the following studies is an example of a longitudinal design? a. Dr. Finn’s study in which he measured job commitment in a group of Japanese factory workers and in a group of Mexican factory workers b. Dr. Stabler’s study in which he measured people’s frequency of playing video games in ninth grade and their aggressive behaviors in 12th grade c. Dr. Benson’s study in which she measured people’s spatial manipulation ability in August and measured their ability again in May after they had taken two semesters of art classes d. Dr. Tutola’s study in which he measured the daily stress of a group of married men and the daily happiness of their spouses 2. Which of the following is a necessary component of a longitudinal design? a. Measuring the same variables at two points in time b. Measuring at least four variables at one time c. Measuring different age groups at two different times d. Manipulating a variable at two points in time 3. _________ can be examined in both simple bivariate designs and longitudinal designs. a. Autocorrelation b. Cross-sectional correlation c. Cross-lag correlation d. Sequential correlation 4. When conducting longitudinal research, researchers typically find _________ to be the most interesting. a. autocorrelations b. cross-sectional correlations c. cross-lag correlations d. multivariate correlations 5. Cross-lag correlations are NOT helpful for answering/addressing which rule of causation? a. Rule of covariance: Is there covariance? b. Rule of temporal precedence: Is there temporal precedence? c. Are there third variables that could explain the relationship? d. Rule of parsimony 6. RESEARCH STUDY 9.1: Dr. Farah is an educational psychologist who is interested in studying the potential causal relationship between doing homework and academic achievement. In January, Dr. Farah has her students report their fall GPA (a measure of academic achievement) and estimate how many hours they spent doing homework during a typical week in the fall semester. In May, Dr. Farah measures the same variables again (the estimated number of hours spent doing homework during a typical week in the spring semester and their spring GPA). She finds the following correlations. Variable A Variable B Correlation Coefficient Correlation 1 Fall number of hours of homework Fall semester GPA .83* Correlation 2 Fall number of hours of homework Spring number of hours of Homework .36* Correlation 3 Fall number of hours of homework Spring semester GPA .69* Correlation 4 Fall semester GPA Spring number of hours of Homework .18 Correlation 5 Fall semester GPA Spring semester GPA .45* Correlation 6 Spring number of hours of homework Spring semester GPA .80* *Indicates a statistically significant relationship. What type of study design is Dr. Farah using? a. Quasi-experimental design b. Bivariate correlational design c. Multiple regression design d. Longitudinal design 7. RESEARCH STUDY 9.1: Dr. Farah is an educational psychologist who is interested in studying the potential causal relationship between doing homework and academic achievement. In January, Dr. Farah has her students report their fall GPA (a measure of academic achievement) and estimate how many hours they spent doing homework during a typical week in the fall semester. In May, Dr. Farah measures the same variables again (the estimated number of hours spent doing homework during a typical week in the spring semester and their spring GPA). She finds the following correlations. Variable A Variable B Correlation Coefficient Correlation 1 Fall number of hours of homework Fall semester GPA .83* Correlation 2 Fall number of hours of homework Spring number of hours of homework .36* Correlation 3 Fall number of hours of homework Spring semester GPA .69* Correlation 4 Fall semester GPA Spring number of hours of Homework .18 Correlation 5 Fall semester GPA Spring semester GPA .45* Correlation 6 Spring number of hours of homework Spring semester GPA .80* *Indicates a statistically significant relationship. In considering the three criteria for causation, which of the following questions will Dr. Farah’s study NOT be able to address? a. Is there covariance? b. Is there temporal precedence? c. Are there third variables that could explain the relationship? d. Do the rules make intuitive sense? 8. RESEARCH STUDY 9.1: Dr. Farah is an educational psychologist who is interested in studying the potential causal relationship between doing homework and academic achievement. In January, Dr. Farah has her students report their fall GPA (a measure of academic achievement) and estimate how many hours they spent doing homework during a typical week in the fall semester. In May, Dr. Farah measures the same variables again (the estimated number of hours spent doing homework during a typical week in the spring semester and their spring GPA). She finds the following correlations. Variable A Variable B Correlation Coefficient Correlation 1 Fall number of hours of homework Fall semester GPA .83* Correlation 2 Fall number of hours of homework Spring number of hours of homework .36* Correlation 3 Fall number of hours of homework Spring semester GPA .69* Correlation 4 Fall semester GPA Spring number of hours of homework .18 Correlation 5 Fall semester GPA Spring semester GPA .45* Correlation 6 Spring number of hours of homework Spring semester GPA .80* *Indicates a statistically significant relationship. Which of the correlations is an autocorrelation? a. Correlation 1 b. Correlation 2 c. Correlation 4 d. Correlation 6 9. RESEARCH STUDY 9.1: Dr. Farah is an educational psychologist who is interested in studying the potential causal relationship between doing homework and academic achievement. In January, Dr. Farah has her students report their fall GPA (a measure of academic achievement) and estimate how many hours they spent doing homework during a typical week in the fall semester. In May, Dr. Farah measures the same variables again (the estimated number of hours spent doing homework during a typical week in the spring semester and their spring GPA). She finds the following correlations. Variable A Variable B Correlation Coefficient Correlation 1 Fall number of hours of homework Fall semester GPA .83* Correlation 2 Fall number of hours of homework Spring number of hours of Homework .36* Correlation 3 Fall number of hours of homework Spring semester GPA .69* Correlation 4 Fall semester GPA Spring number of hours of Homework .18 Correlation 5 Fall semester GPA Spring semester GPA .45* Correlation 6 Spring number of hours of homework Spring semester GPA .80* *Indicates a statistically significant relationship. Of the correlations listed in the table, how many are autocorrelations? a. Two b. Three c. Four d. Five 10. RESEARCH STUDY 9.1: Dr. Farah is an educational psychologist who is interested in studying the potential causal relationship between doing homework and academic achievement. In January, Dr. Farah has her students report their fall GPA (a measure of academic achievement) and estimate how many hours they spent doing homework during a typical week in the fall semester. In May, Dr. Farah measures the same variables again (the estimated number of hours spent doing homework during a typical week in the spring semester and their spring GPA). She finds the following correlations. Variable A Variable B Correlation Coefficient Correlation 1 Fall number of hours of homework Fall semester GPA .83* Correlation 2 Fall number of hours of homework Spring number of hours of Homework .36* Correlation 3 Fall number of hours of homework Spring semester GPA .69* Correlation 4 Fall semester GPA Spring number of hours of Homework .18 Correlation 5 Fall semester GPA Spring semester GPA .45* Correlation 6 Spring number of hours of homework Spring semester GPA .80* *Indicates a statistically significant relationship. Which of the following correlations is a cross-sectional correlation? a. Correlation 3 b. Correlation 4 c. Correlation 5 d. Correlation 6 11. RESEARCH STUDY 9.1: Dr. Farah is an educational psychologist who is interested in studying the potential causal relationship between doing homework and academic achievement. In January, Dr. Farah has her students report their fall GPA (a measure of academic achievement) and estimate how many hours they spent doing homework during a typical week in the fall semester. In May, Dr. Farah measures the same variables again (the estimated number of hours spent doing homework during a typical week in the spring semester and their spring GPA). She finds the following correlations. Variable A Variable B Correlation Coefficient Correlation 1 Fall number of hours of homework Fall semester GPA .83* Correlation 2 Fall number of hours of homework Spring number of hours of homework .36* Correlation 3 Fall number of hours of homework Spring semester GPA .69* Correlation 4 Fall semester GPA Spring number of hours of homework .18 Correlation 5 Fall semester GPA Spring semester GPA .45* Correlation 6 Spring number of hours of homework Spring semester GPA .80* *Indicates a statistically significant relationship. Of the correlations listed, how many are cross-sectional correlations? a. One b. Two c. Three d. Four 12. RESEARCH STUDY 9.1: Dr. Farah is an educational psychologist who is interested in studying the potential causal relationship between doing homework and academic achievement. In January, Dr. Farah has her students report their fall GPA (a measure of academic achievement) and estimate how many hours they spent doing homework during a typical week in the fall semester. In May, Dr. Farah measures the same variables again (the estimated number of hours spent doing homework during a typical week in the spring semester and their spring GPA). She finds the following correlations. Variable A Variable B Correlation Coefficient Correlation 1 Fall number of hours of homework Fall semester GPA .83* Correlation 2 Fall number of hours of homework Spring number of hours of homework .36* Correlation 3 Fall number of hours of homework Spring semester GPA .69* Correlation 4 Fall semester GPA Spring number of hours of homework .18 Correlation 5 Fall semester GPA Spring semester GPA .45* Correlation 6 Spring number of hours of homework Spring semester GPA .80* *Indicates a statistically significant relationship. Which of the following correlations is a cross-lag correlation? a. Both Correlations 1 and 6 b. Both Correlations 2 and 5 c. Both Correlations 3 and 4 d. Both Correlations 3 and 5 13. RESEARCH STUDY 9.1: Dr. Farah is an educational psychologist who is interested in studying the potential causal relationship between doing homework and academic achievement. In January, Dr. Farah has her students report their fall GPA (a measure of academic achievement) and estimate how many hours they spent doing homework during a typical week in the fall semester. In May, Dr. Farah measures the same variables again (the estimated number of hours spent doing homework during a typical week in the spring semester and their spring GPA). She finds the following correlations. Variable A Variable B Correlation Coefficient Correlation 1 Fall number of hours of homework Fall semester GPA .83* Correlation 2 Fall number of hours of homework Spring number of hours of homework .36* Correlation 3 Fall number of hours of homework Spring semester GPA .69* Correlation 4 Fall semester GPA Spring number of hours of homework .18 Correlation 5 Fall semester GPA Spring semester GPA .45* Correlation 6 Spring number of hours of homework Spring semester GPA .80* *Indicates a statistically significant relationship. Correlation 4 is an example of which of the following types of correlations? a. Autocorrelation b. Multivariate correlation c. Cross-sectional correlation d. Cross-lag correlation 14. RESEARCH STUDY 9.1: Dr. Farah is an educational psychologist who is interested in studying the potential causal relationship between doing homework and academic achievement. In January, Dr. Farah has her students report their fall GPA (a measure of academic achievement) and estimate how many hours they spent doing homework during a typical week in the fall semester. In May, Dr. Farah measures the same variables again (the estimated number of hours spent doing homework during a typical week in the spring semester and their spring GPA). She finds the following correlations. Variable A Variable B Correlation Coefficient Correlation 1 Fall number of hours of homework Fall semester GPA .83* Correlation 2 Fall number of hours of homework Spring number of hours of homework .36* Correlation 3 Fall number of hours of homework Spring semester GPA .69* Correlation 4 Fall semester GPA Spring number of hours of homework .18 Correlation 5 Fall semester GPA Spring semester GPA .45* Correlation 6 Spring number of hours of homework Spring semester GPA .80* *Indicates a statistically significant relationship. Correlation 1 is an example of which of the following types of correlations? a. Autocorrelation b. Multivariate correlation c. Cross-sectional correlation d. Cross-lag correlation 15. RESEARCH STUDY 9.1: Dr. Farah is an educational psychologist who is interested in studying the potential causal relationship between doing homework and academic achievement. In January, Dr. Farah has her students report their fall GPA (a measure of academic achievement) and estimate how many hours they spent doing homework during a typical week in the fall semester. In May, Dr. Farah measures the same variables again (the estimated number of hours spent doing homework during a typical week in the spring semester and their spring GPA). She finds the following correlations. Variable A Variable B Correlation Coefficient Correlation 1 Fall number of hours of homework Fall semester GPA .83* Correlation 2 Fall number of hours of homework Spring number of hours of Homework .36* Correlation 3 Fall number of hours of homework Spring semester GPA .69* Correlation 4 Fall semester GPA Spring number of hours of Homework .18 Correlation 5 Fall semester GPA Spring semester GPA .45* Correlation 6 Spring number of hours of homework Spring semester GPA .80* *Indicates a statistically significant relationship. Correlation 5 is an example of which of the following types of correlations? a. Autocorrelation b. Multivariate correlation c. Cross-sectional correlation d. Cross-lag correlation 16. RESEARCH STUDY 9.1: Dr. Farah is an educational psychologist who is interested in studying the potential causal relationship between doing homework and academic achievement. In January, Dr. Farah has her students report their fall GPA (a measure of academic achievement) and estimate how many hours they spent doing homework during a typical week in the fall semester. In May, Dr. Farah measures the same variables again (the estimated number of hours spent doing homework during a typical week in the spring semester and their spring GPA). She finds the following correlations. Variable A Variable B Correlation Coefficient Correlation 1 Fall number of hours of homework Fall semester GPA .83* Correlation 2 Fall number of hours of homework Spring number of hours of homework .36* Correlation 3 Fall number of hours of homework Spring semester GPA .69* Correlation 4 Fall semester GPA Spring number of hours of homework .18 Correlation 5 Fall semester GPA Spring semester GPA .45* Correlation 6 Spring number of hours of homework Spring semester GPA .80* *Indicates a statistically significant relationship. Based on her pattern of correlations, which of the following can Dr. Farah safely conclude? a. Because Correlation 3 is significant but Correlation 4 is not, Dr. Farah has evidence that increased homework comes before academic achievement. b. Because not all the correlations are significant, Dr. Farah has no evidence that increased homework comes before academic achievement. c. Because Correlations 2 and 3 are significant, Dr. Farah has evidence that increased homework comes before academic achievement. d. Because Correlation 4 is stronger than Correlation 5, Dr. Farah has no evidence that increased homework comes before academic achievement. 17. RESEARCH STUDY 9.1: Dr. Farah is an educational psychologist who is interested in studying the potential causal relationship between doing homework and academic achievement. In January, Dr. Farah has her students report their fall GPA (a measure of academic achievement) and estimate how many hours they spent doing homework during a typical week in the fall semester. In May, Dr. Farah measures the same variables again (the estimated number of hours spent doing homework during a typical week in the spring semester and their spring GPA). She finds the following correlations. Variable A Variable B Correlation Coefficient Correlation 1 Fall number of hours of homework Fall semester GPA .83* Correlation 2 Fall number of hours of homework Spring number of hours of Homework .36* Correlation 3 Fall number of hours of homework Spring semester GPA .69* Correlation 4 Fall semester GPA Spring number of hours of Homework .18 Correlation 5 Fall semester GPA Spring semester GPA .45* Correlation 6 Spring number of hours of homework Spring semester GPA .80* *Indicates a statistically significant relationship. For Dr. Farah to make the claim that homework causes academic achievement, which correlation does she predict will NOT be significant? a. Correlation 1 b. Correlation 2 c. Correlation 3 d. Correlation 4 18. RESEARCH STUDY 9.1: Dr. Farah is an educational psychologist who is interested in studying the potential causal relationship between doing homework and academic achievement. In January, Dr. Farah has her students report their fall GPA (a measure of academic achievement) and estimate how many hours they spent doing homework during a typical week in the fall semester. In May, Dr. Farah measures the same variables again (the estimated number of hours spent doing homework during a typical week in the spring semester and their spring GPA). She finds the following correlations. Variable A Variable B Correlation Coefficient Correlation 1 Fall number of hours of homework Fall semester GPA .83* Correlation 2 Fall number of hours of homework Spring number of hours of Homework .36* Correlation 3 Fall number of hours of homework Spring semester GPA .69* Correlation 4 Fall semester GPA Spring number of hours of Homework .18 Correlation 5 Fall semester GPA Spring semester GPA .45* Correlation 6 Spring number of hours of homework Spring semester GPA .80* *Indicates a statistically significant relationship. Imagine that Dr. Farah noted a cyclical, reinforcing relationship between homework and academic achievement. For this to be case, which of the following correlations would need to be significant? a. Correlations 1 and 6 b. Correlations 2 and 5 c. Correlations 3 and 4 d. Correlations 2 and 3 19. RESEARCH STUDY 9.1: Dr. Farah is an educational psychologist who is interested in studying the potential causal relationship between doing homework and academic achievement. In January, Dr. Farah has her students report their fall GPA (a measure of academic achievement) and estimate how many hours they spent doing homework during a typical week in the fall semester. In May, Dr. Farah measures the same variables again (the estimated number of hours spent doing homework during a typical week in the spring semester and their spring GPA). She finds the following correlations. Variable A Variable B Correlation Coefficient Correlation 1 Fall number of hours of homework Fall semester GPA .83* Correlation 2 Fall number of hours of homework Spring number of hours of Homework .36* Correlation 3 Fall number of hours of homework Spring semester GPA .69* Correlation 4 Fall semester GPA Spring number of hours of Homework .18 Correlation 5 Fall semester GPA Spring semester GPA .45* Correlation 6 Spring number of hours of homework Spring semester GPA .80* *Indicates a statistically significant relationship. A colleague of Dr. Farah’s questions the internal validity of her causal claim. He is curious as to whether the relationship between homework and academic achievement could be explained by interest in one’s classes. Specifically, he thinks that students who are interested in their classes will both do more homework and have higher GPAs. Which of the following is a solution to this possible threat to internal validity? a. Dr. Farah should replicate her study. b. Dr. Farah should also measure students’ interest in their class. c. Dr. Farah should measure students’ interest in their class instead of time spent doing homework. d. Dr. Farah should measure students’ interest in their class instead of GPA. 20. RESEARCH STUDY 9.1: Dr. Farah is an educational psychologist who is interested in studying the potential causal relationship between doing homework and academic achievement. In January, Dr. Farah has her students report their fall GPA (a measure of academic achievement) and estimate how many hours they spent doing homework during a typical week in the fall semester. In May, Dr. Farah measures the same variables again (the estimated number of hours spent doing homework during a typical week in the spring semester and their spring GPA). She finds the following correlations. Variable A Variable B Correlation Coefficient Correlation 1 Fall number of hours of homework Fall semester GPA .83* Correlation 2 Fall number of hours of homework Spring number of hours of Homework .36* Correlation 3 Fall number of hours of homework Spring semester GPA .69* Correlation 4 Fall semester GPA Spring number of hours of Homework .18 Correlation 5 Fall semester GPA Spring semester GPA .45* Correlation 6 Spring number of hours of homework Spring semester GPA .80* *Indicates a statistically significant relationship. A colleague of Dr. Farah’s asks her why she did not simply conduct an experiment. Which of the following is a probable reason for Dr. Farah’s choice not to conduct an experiment? a. It would be impossible to manipulate hours of homework completed. b. It would be too costly/expensive to run an experiment. c. It would be unethical to manipulate whether students are told to do homework for a semester. d. It would take longer to conduct an experiment. 21. In understanding “controlling for” a third variable, which of the following is a similar concept? a. Creating a longitudinal study b. Identifying subgroups c. Creating an operational definition d. Conducting a replication 22. Which popular media headline does NOT suggest that a multiple regression has been used? a. “Dog ownership decreases stress.” b. “After taking into account job experience, people who are happier with their jobs report greater productivity.” c. “After correcting for several factors that affect memory, including intelligence, researchers found that people who read more frequently remember 12% more about a crime scene than those who don’t read frequently.” d. “The link between traumatic experience and the development of anxiety symptoms existed even when controlling for the effect of parental anxiety.” 23. Which popular media headline might suggest that a multiple regression has been used? a. “Pet ownership is an important predictor of well-being in elderly adults.” b. “Daughters are happier when their mothers are happy working outside the home.” c. “Eating lunch away from your desk is associated with greater work productivity.” d. “Vacations are important for happiness, even when length of vacation is controlled for.” 24. In a multiple regression design, _________ variable is to dependent variable as _________variable is to independent variable. a. criterion; predictor b. manipulated; measured c. control; mediator d. bivariate; multivariate 25. All of the following are true of betas and correlation coefficients EXCEPT: a. Betas describe the relationship between two variables exactly as correlations coefficients do. b. Both betas and correlation coefficients can tell you something about the strength of a relationship. c. Both betas and correlation coefficients can tell you something about the direction of a relationship. d. Betas from an analysis can be compared with other beta coefficients from the same analysis just as correlation coefficients can. 26. Which of the following is a reason why multiple regression designs are inferior to experimental designs? a. They can only control for third variables that are measured. b. They cannot establish covariance. c. They take longer to conduct. d. They are more expensive to conduct. 27. RESEARCH STUDY 9.2: Dr. Finkel is a social psychologist who studies romantic relationships. Several researchers have found that there is a link between income and marital satisfaction (e.g., Dakin & Wampler, 2012). Dr. Finkel is curious as to whether there is a causal link between the two variables, such that having a higher income causes higher levels of marital satisfaction. He is confident that he cannot reasonably or ethically manipulate people’s income level, so he decides to use a multivariate design. He is also curious as to whether there is a causal link between these two variables or if two other variables (number of arguments and life satisfaction) can explain the relationship. He measures his three variables in a sample of 124 married couples recruited from a local community center. Below are his results. DV: Marital Satisfaction Variable Beta () Significance () Income .69 .03 Number of arguments .73 .01 Life satisfaction .13 .81 Given Dr. Finkel’s design, which of the following issues is his study best able to address? a. The ethical issue of manipulating income level b. The issue of temporal precedence between his two variables c. The issue of possible third variables d. The issue of diminished statistical validity 28. RESEARCH STUDY 9.2: Dr. Finkel is a social psychologist who studies romantic relationships. Several researchers have found that there is a link between income and marital satisfaction (e.g., Dakin & Wampler, 2012). Dr. Finkel is curious as to whether there is a causal link between the two variables, such that having a higher income causes higher levels of marital satisfaction. He is confident that he cannot reasonably or ethically manipulate people’s income level, so he decides to use a multivariate design. He is also curious as to whether there is a causal link between these two variables or if two other variables (number of arguments and life satisfaction) can explain the relationship. He measures his three variables in a sample of 124 married couples recruited from a local community center. Below are his results. DV: Marital Satisfaction Variable Beta () Significance () Income .69 .03 Number of arguments .73 .01 Life satisfaction .13 .81 Which of the following is NOT a predictor variable in Dr. Finkel’s study? a. Marital satisfaction b. Life satisfaction c. Income d. Number of arguments 29. RESEARCH STUDY 9.2: Dr. Finkel is a social psychologist who studies romantic relationships. Several researchers have found that there is a link between income and marital satisfaction (e.g., Dakin & Wampler, 2012). Dr. Finkel is curious as to whether there is a causal link between the two variables, such that having a higher income causes higher levels of marital satisfaction. He is confident that he cannot reasonably or ethically manipulate people’s income level, so he decides to use a multivariate design. He is also curious as to whether there is a causal link between these two variables or if two other variables (number of arguments and life satisfaction) can explain the relationship. He measures his three variables in a sample of 124 married couples recruited from a local community center. Below are his results. DV: Marital Satisfaction Variable Beta () Significance () Income .69 .03 Number of arguments .73 .01 Life satisfaction .13 .81 Which of the following can be concluded based on the results of Dr. Finkel’s study? a. As the number of arguments a couple has increases, their marital satisfaction increases as well, controlling for income but not life satisfaction. b. The relationship between life satisfaction and marital satisfaction has the weakest effect size of all of the results. c. The beta for the relationship between life satisfaction and marital satisfaction is significantly different than zero. d. Income is a stronger predictor of martial satisfaction than either the number of arguments or life satisfaction. 30. RESEARCH STUDY 9.2: Dr. Finkel is a social psychologist who studies romantic relationships. Several researchers have found that there is a link between income and marital satisfaction (e.g., Dakin & Wampler, 2012). Dr. Finkel is curious as to whether there is a causal link between the two variables, such that having a higher income causes higher levels of marital satisfaction. He is confident that he cannot reasonably or ethically manipulate people’s income level, so he decides to use a multivariate design. He is also curious as to whether there is a causal link between these two variables or if two other variables (number of arguments and life satisfaction) can explain the relationship. He measures his three variables in a sample of 124 married couples recruited from a local community center. Below are his results. DV: Marital Satisfaction Variable Beta () Significance () Income .69 .03 Number of arguments .73 .01 Life satisfaction .13 .81 One of Dr. Finkel’s colleagues argues that he should have considered years of marriage in his study, which is a known predictor of marital satisfaction. If Dr. Finkel conducts his study again and asks people to report on how many years they have been married as well, which of the following statements is true? a. The beta value for number of arguments may no longer be statistically significant. b. The beta value for number of arguments will remain unchanged. c. He will need to add another criterion variable. d. He will need to delete a predictor variable. 31. RESEARCH STUDY 9.2: Dr. Finkel is a social psychologist who studies romantic relationships. Several researchers have found that there is a link between income and marital satisfaction (e.g., Dakin & Wampler, 2012). Dr. Finkel is curious as to whether there is a causal link between the two variables, such that having a higher income causes higher levels of marital satisfaction. He is confident that he cannot reasonably or ethically manipulate people’s income level, so he decides to use a multivariate design. He is also curious as to whether there is a causal link between these two variables or if two other variables (number of arguments and life satisfaction) can explain the relationship. He measures his three variables in a sample of 124 married couples recruited from a local community center. Below are his results. DV: Marital Satisfaction Variable Beta () Significance () Income .69 .03 Number of arguments .73 .01 Life satisfaction .13 .81 Which of the following is a criterion variable in Dr. Finkel’s study? a. Marital satisfaction b. Life satisfaction c. Income d. Number of arguments 32. A researcher has examined a variety of correlational studies that point to a causal relationship between two variables. All of the studies have found a positive relationship between the two variables, but for ethical reasons, no experiments have been conducted. Using an approach of pattern and parsimony, the researcher may begin to make a causal claim by doing which of the following? a. Running another correlational study but with more people b. Specifying a mechanism or explanation for the causal relationship c. Examining the dates of the studies to look for temporal precedence d. Replicating all of the original studies 33. The pattern and parsimony approach to causation is a good example of which cycle in research? a. Journal-journalism cycle b. Basic-applied cycle c. Theory-data cycle d. Peer-review cycle 34. Which of the following is NOT true of third variables and mediating variables? a. Third variables are external to the causal variable, but mediating variables are internal to the causal variable. b. Third variables are considered nuisances, but mediating variables are not. c. Third variables can be detected using multiple regression techniques, but mediating variables cannot. d. Third variables are not usually of central interest to researchers, but mediating variables are. 35. RESEARCH STUDY 9.3: Dr. Cheong is a clinical psychologist who is curious about how people deal with natural disasters (e.g., hurricanes, tornados, earthquakes). His previous research suggests that there is a relationship between how much people feel their emotional well-being was affected by the natural disaster and their likelihood of developing posttraumatic stress disorder (PTSD) symptoms. However, he is curious as to whether the effect of emotional well-being occurs because people receive different levels of social support. He conducts a study in which he asks 174 men and women affected by Hurricane Sandy (2012) to report on how their well-being was affected by the hurricane, the social support felt after the storm, and the number of PTSD symptoms. Dr. Cheong finds support for his proposed relationship. However, in examining his data more closely, he finds that the relationship between emotional well-being and PTSD symptoms is stronger for men than for women. Which of the following is the mediating variable in Dr. Cheong’s hypothesis? a. Emotional well-being b. PTSD symptoms c. Social support d. Participant sex 36. RESEARCH STUDY 9.3: Dr. Cheong is a clinical psychologist who is curious about how people deal with natural disasters (e.g., hurricanes, tornados, earthquakes). His previous research suggests that there is a relationship between how much people feel their emotional well-being was affected by the natural disaster and their likelihood of developing posttraumatic stress disorder (PTSD) symptoms. However, he is curious as to whether the effect of emotional well-being occurs because people receive different levels of social support. He conducts a study in which he asks 174 men and women affected by Hurricane Sandy (2012) to report on how their well-being was affected by the hurricane, the social support felt after the storm, and the number of PTSD symptoms. Dr. Cheong finds support for his proposed relationship. However, in examining his data more closely, he finds that the relationship between emotional well-being and PTSD symptoms is stronger for men than for women. Dr. Cheong’s finding that the relationship between emotional well-being and PTSD symptoms is stronger for men than for women suggests which of the following? a. Participant sex is a moderating variable. b. Participant sex is a mediating variable. c. Emotional well-being is a moderating variable. d. Emotional well-being is a mediating variable. 37. Which of the following is true of multiple regression? a. It can control for all third variables, including those that are not measured. b. Adding more predictors means research is controlling for more variables. c. There is a limit to the number of predictors that can be statistically significant. d. There is a limit to the number of predictors that can be included in a regression. 38. Why is the statistical validity of a multiple regression design more complicated to interrogate than a bivariate design? a. Statistical significance of associations cannot be determined. b. Betas and rs share no similarities. c. These designs require more participants. d. It is harder to detect outliers. 39. If a researcher is asking why the relationship between two variables exists, she is curious about which of the following? a. Moderation b. Mediation c. Third variables d. Controlling variables 40. When determining mediation, how many steps are necessary? a. Two b. Three c. Four d. Five 41. Why would a researcher interested in making a causal claim NOT do an experiment? a. Experiments are very expensive and the researcher might not have grant funding. b. There may be ethical limitations of manipulating a variable. c. Laboratory space is required for experiments and the researcher might not have a lab. d. Experiments take longer to do than other types of studies. 42. If an experiment cannot be done for practical or ethical reasons related to manipulating the variable of interest, which of the following events should happen? a. The study should not be conducted at all. b. The researchers should wait until the experiment can be done. c. A longitudinal correlational design could be done instead. d. The IRB can grant a waiver of review to conduct the study anyway. 43. A criterion variable is also known as a(n) _________ variable. a. predictor b. independent c. control d. dependent 44. Which of the following words/symbols would indicate that you are reading results from a multiple-regression analysis? a.  (looks like a B) b. Sig c. r d. d 45. Adding several variables to a regression analysis can help do which of the following? a. Increase the statistical significance of the results b. Control for several variables at once c. Increase the construct validity of a study d. Meet the temporal precedence criterion for causal inference 46. The degree to which a good scientific theory provides the simplest explanation of some phenomenon is known as _________. a. minimalism b. pretentiousness c. parsimony d. density 47. Such topics as the link between media and aggression and smoking and lung cancer have been studied with a variety of methods and by a variety of researchers and have all reached similar conclusions. This is an example of which of the following? a. Hypothesis generation b. Third variable problems c. Multiple-regression designs d. Pattern and parsimony 48. Why is it problematic when journalists only report on a single study? a. It can make journalists look bad. b. It can lead people to think journalists are scientists. c. It can lead people to value one study over decades of previous research. d. It can cause people to interrogate a study’s validities. 49. Why should journalists report on the previous body of research when writing about a newly published scientific study? a. To highlight pattern and parsimony in scientific research b. To demonstrate that they have a background in science c. To make it easier for their readers to determine that the story is credible d. To prove to their editors that readers will be interested in the story 50. When examining the results of a multiple regression, which of the following should be compared to determine which predictor variables have the largest relationship to the criterion variable? a. b values b. Beta values c. Significance values d. Effect sizes [Show More]

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