Module 5 Quiz

A  It can lead people to think journalists are scientists.

B  It can make journalists look bad.

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.

A  b

B  r

C  p

D  d

A  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

B  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

C  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

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

A  Statistical significance alone is sufficient to indicate effect size.

B  Larger effect sizes are advantageous for statistical significance.

C  An association’s effect size has no effect on statistical significance.

D  Effect size and statistical significance are synonymous terms.

A  All else being equal, there will be greater likelihood of a finding being important in the real world.

B  All else being equal, there will be a greater likelihood of finding a non-statistically significant relationship.

C  All else being equal, there will be greater likelihood of establishing construct validity.

D  All else being equal, there will be greater likelihood of finding a zero in the 95% CI.

A  The phrase “controlled for” when describing the findings.

B  A list of the specific predictor variables used.

C  A table with the betas and their confidence intervals.

D  A list of the specific criterion variables used.

A  manipulating a variable at two points in time

B  measuring at least four variables at one time

C  measuring different age groups at two different times

D  measuring the same variables at two points in time

A  r = .26, 95% CI [–.08, .60]

B  r = –.28, 95% CI [–.06, –.50]

C  r = .32, 95% CI [.03, .61]

D  r = -.44, 95% CI [–.32, –.56]

A  They are different: A moderator only involves one variable, while a spurious association involves both variables.

B  They are the same: A moderator indicates that the association is spurious.

C  They are different: A moderator indicates that the same association exists within subgroups, while a spurious association indicates that the associations differ for subgroups.

D  They are different: A moderator indicates the association is not spurious.

A  b values

B  beta values

C  significance values

D  effect sizes

A  a scatterplot

B  an outlier

C  a bar graph

D  a curvilinear association

A  a difference in the height between the bars

B  the number of observations that make each bar

C  the number of bars in the graph

D  the direction of the bars

A  cross-sectional correlations

B  autocorrelations

C  multivariate correlations

D  cross-lag correlations

A  causal inferences; made

B  covariance; established

C  construct validity; interrogated

D  hypotheses; tested

A  third variable

B  covariance

C  association

D  directionality

A  third variable problems

B  multiple-regression designs

C  hypothesis generation

D  pattern and parsimony

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

A  emotional well-being is a moderating variable.

B  participant gender is a moderating variable.

C  emotional well-being is a mediating variable.

D  participant gender is a mediating variable.

A  spurious variable.

B  outlier.

C  moderator.

D  cause.

A  sample size and effect size

B  the number of outliers and the direction of the association

C  sample size and number of variables analyzed

D  direction of the association and strength of the association

A  random.

B  outliers.

C  curvilinear scores.

D  moderators.

A  life satisfaction, experiences of daily stress, and number of friends one has simultaneously

B  life satisfaction and experience of daily stress

C  number of friends one has and life satisfaction

D  number of friends one has and experience of daily stress

A  The association found in her study could probably generalize to young adults.

B  The association found in her study could probably generalize to people living in other capital cities (e.g., Sacramento, California).

C  The association found in her study could probably generalize to elderly people in other large cities in the South.

D  The association found in her study could probably generalize to elderly persons living in nursing homes.

A  outlier.

B  cause.

C  moderator.

D  spurious variable.

A  cross-sectional

B  longitudinal

C  autocorrelational

D  cross-lag correlations

A  an outlier effect.

B  restriction of range.

C  null effect.

D  spurious data.

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.

A  third variables

B  moderation

C  controlling variables

D  mediation

A  The third variable must be measured on the same scale as the original measured variables.

B  The third variable must be a categorical variable.

C  The third variable must have a positive relationship with the two measured variables in the original association.

D  The third variable must be related to both of the measured variables in the original association.

A  He should find that the interval contains a zero for his first study.

B  He should find that the interval is wider for his first study.

C  He should find that the interval contains a zero for his second study.

D  He should find that the interval is wider for his second study.

A  both betas and correlation coefficients can tell you something about the strength of a relationship.

B  both betas and correlation coefficients can tell you something about the direction of a relationship.

C  betas describe the relationship between two variables exactly as correlations coefficients do.

D  betas from an analysis can be compared with other beta coefficients from the same analysis just as correlation coefficients can.

A  predictor.

B  mediator.

C  criterion.

D  moderator.

A  examining the dates of the studies to look for temporal precedence

B  specifying a mechanism or explanation for the causal relationship

C  running another correlational study but with more people

D  replicating all of the original studies

A  The 95% CI for that beta contains zero.

B  The 95% CI for that beta indicates a positive association.

C  The 95% CI for that beta is not significant.

D  The 95% CI for that beta does not contain zero.

A  dependent

B  predictor

C  control

D  independent