Module 5 Quiz

A  It can cause people to interrogate a study’s validities.

B  It can make journalists look bad.

C  It can lead people to think journalists are scientists.

D  It can lead people to value one study over decades of previous research.

A  p

B  r

C  b

D  d

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. Tutola’s study in which he measured the daily stress of a group of married men and the daily happiness of their spouses

D  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

A  Effect size and statistical significance are synonymous terms.

B  Larger effect sizes are advantageous for statistical significance.

C  Statistical significance alone is sufficient to indicate effect size.

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

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 greater likelihood of finding a zero in the 95% CI.

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

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

A  A list of the specific predictor variables used.

B  A list of the specific criterion variables used.

C  A table with the betas and their confidence intervals.

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

A  manipulating a variable at two points in time

B  measuring the same variables at two points in time

C  measuring at least four variables at one time

D  measuring different age groups at two different times

A  r = -.44, 95% CI [–.32, –.56]

B  r = .32, 95% CI [.03, .61]

C  r = –.28, 95% CI [–.06, –.50]

D  r = .26, 95% CI [–.08, .60]

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

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

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

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

A  beta values

B  b values

C  significance values

D  effect sizes

A  a scatterplot

B  a bar graph

C  a curvilinear association

D  an outlier

A  the number of observations that make each bar

B  a difference in the height between the bars

C  the number of bars in the graph

D  the direction of the bars

A  autocorrelations

B  multivariate correlations

C  cross-lag correlations

D  cross-sectional correlations

A  causal inferences; made

B  hypotheses; tested

C  covariance; established

D  construct validity; interrogated

A  directionality

B  third variable

C  covariance

D  association

A  pattern and parsimony

B  third variable problems

C  multiple-regression designs

D  hypothesis generation

A  number of outliers and direction of the association

B  sample size and effect size

C  sample size and number of variables analyzed

D  direction of the association and strength of the association

A  participant gender is a mediating variable.

B  emotional well-being is a moderating variable.

C  participant gender is a moderating variable.

D  emotional well-being is a mediating variable.

A  moderator.

B  spurious variable.

C  outlier.

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  curvilinear scores.

B  moderators.

C  outliers.

D  random.

A  life satisfaction and experience of daily stress

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

C  number of friends one has and experience of daily stress

D  number of friends one has and life satisfaction

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

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

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

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

A  cause.

B  moderator.

C  outlier.

D  spurious variable.

A  longitudinal

B  cross-lag correlations

C  cross-sectional

D  autocorrelational

A  null effect.

B  restriction of range.

C  spurious data.

D  an outlier effect.

A  The effect size should be considered, but tests of statistical significance should not.

B  The findings should be replicated in another population.

C  The study must be done again using the same participants.

D  The association should be rejected as inconclusive.

A  mediation

B  third variables

C  controlling variables

D  moderation

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

B  The third variable must be a categorical variable.

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

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

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

B  He should find that the interval contains a zero 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 first 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 from an analysis can be compared with other beta coefficients from the same analysis just as correlation coefficients can.

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

A  predictor.

B  mediator.

C  moderator.

D  criterion.

A  running another correlational study but with more people

B  specifying a mechanism or explanation for the causal relationship

C  replicating all of the original studies

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

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

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

C  The 95% CI for that beta contains zero.

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

A  control

B  dependent

C  predictor

D  independent