In a between-subjects design, individual differences (participant variables) are a problem because they can ____.
a. become confounding variables
b. decrease variability of the scores
c. preclude the use of statistical analyses
d. produce fatigue effects
The consistency of an observation from one time to another is referred to as ____ reliability.
a. inter-rater
b. test-retest
c. parallel-forms
d. internal consistency
Fudging data refers to
a. refusing to comply with IRB requirements.
b. manipulating results to improve their appearance.
c. reporting observations that were not actually made.
d. failing to replicate one's findings.
The nonparametric equivalent to the one-way randomized ANOVA is the _____ test.
a. Chi-square
b. Friedman test
c. r2
d. Kruskal-Wallis
Holding a variable constant prevents a participant characteristic from becoming a confound by ____.
a. eliminating variability in that characteristic
b. reducing error
c. ensuring a nonbiased sample
d. increasing the differences between the groups
The degree to which different observers give consistent estimates of the same phenomenon is referred to as ____ reliability.
a. inter-rater
b. test-retest
c. parallel-forms
d. internal consistency
__________ means that the investigator explains the general purposes of the research and answers any questions of the participant at the end of the experiment.
a. Informed consent
b. Debriefing
c. Freedom to withdraw
d. Confidentiality
The _____ is a nonparametric inferential test for comparing sample medians of two independent groups of scores.
a. Wilcoxon matched-pairs signed-ranks T test
b. Wilcoxon rank-sum test
c. 2 test for independence
d. 2 goodness-of-fit test
Holding a participant characteristic (such as age or gender) constant strengthens ____ and weakens ____.
a. internal validity; external validity
b. external validity; internal validity
c. reliability; validity
d. accuracy; reliability
When there is no error in measurement, reliability is ____.
a. 0
b. 1
c. equal to the variability of the distribution
d. equal to the inverse of the variability of the distribution
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