Ch.17 Analysis Of Variance (Repeated Measures) Test Bank - Statistics 11th Edition Test Questions and Answer Key by Robert S. Witte. DOCX document preview.
MULTIPLE‑CHOICE TEST ITEMS
CHAPTER 17
ANALYSIS OF VARIANCE (REPEATED MEASURES)
17.1 When differences between groups are based on repeated measures, variability due to individual differences is
a) eliminated.
b) reduced.
c) minimized.
d) transformed.
17.2 When used properly, a repeated-measures design
a) decreases the probability of a type I error
b) creates a more powerful analysis.
c) eliminates a number of crucial assumptions.
d) generates more defensible conclusions.
17.3 The distinctive feature of repeated-measures ANOVA is the use of multiple
a) dependent variables.
b) groups.
c) measures on the same subjects.
d) subjects.
17.4 Repeated-measures ANOVA eliminates a most important type of random error, namely that error due to
a) individual differences.
b) measurement deficiencies.
c) equipment breakdowns.
d) any uncontrolled factors.
17.5 When individual differences are removed, the error term in the denominator of the F ratio becomes disproportionately smaller, causing an increased likelihood of
a) retaining a true null hypothesis.
b) rejecting a true null hypothesis.
c) retaining a false null hypothesis.
d) rejecting a false null hypothesis.
17.6 Given the following three possible outcomes,
OUTCOME I
Level 1 Level 2 Level 3
SUBJECT A 2 4 5
SUBJECT B 2 4 5
SUBJECT C 2 4 5
OUTCOME I I
Level 1 Level 2 Level 3
SUBJECT A 4 4 5
SUBJECT B 2 1 4
SUBJECT C 0 2 2
OUTCOME III
Level 1 Level 2 Level 3
SUBJECT A 2 0 2
SUBJECT B 5 5 9
SUBJECT C 9 8 9
the most variability due to individual differences appears in Outcome
a) I.
b) II.
c) III.
d) II or III, depending on which totals are emphasized.
17.7 Generally speaking, when compared with that for non-repeated (independent) measures, the denominator term in the F ratio for repeated measures is
a) larger.
b) the same.
c) virtually the same.
d) smaller.
17.8 When individual differences are very small, the beneficial effects of repeated-measures ANOVA are
a) small.
b) moderate.
c) large.
d) difficult to ascertain.
17.9 Do not use repeated measures if there is a concern about
a) the availability of subjects.
b) a potential bias because of the order in which conditions are experienced.
c) earlier effects lingering during subsequent sessions.
d) about the adequacy of the research hypothesis.
17.10 In repeated-measures ANOVA, the within group sum of squares equals the sum of the
a) within subjects and error sum of squares.
b) between subjects and error sum of squares.
c) within subjects and between subjects.
d) between subjects and between groups.
17.11 It is most efficient to calculate sums of squares terms by using
a) either means or totals.
b) means but not totals.
c) totals but not means.
d) means and totals simultaneously.
17.12 When calculating sums of squares terms with totals,
a) add each total, then divide by its sample size.
b) square each total , then divide by its sample size.
c) add each total, then multiply by its sample size.
d) square each total, then multiply by its sample size.
17.13 In repeated-measures ANOVA, the error sum of squares equals the within sum of squares
a) and the subject sums of squares.
b) and the between group sums of squares.
c) minus the subject sum of squares.
d) minus the between group sum of squares.
17.14 In repeated-measures ANOVA, an F ratio involving 
is not calculated because it would
a) detract from the important F ratio involving 
.
b) culminate in the trivial rejection of the null hypothesis for individual differences.
c) compromise the accuracy of the analysis.
d) supply a false view of individual differences.
17.15 In repeated-measures ANOVA, the partial squared curvilinear correlation always excludes one sum of squares term from its denominator, that is, the _______ sum of squares.
a) total.
b) between.
c) subject.
d) error.
17.16 You would most prefer a partial squared curvilinear correlation equal to
a) .80
b) .60
c) .40
d) .20
17.17 In repeated-measures ANOVA, to pinpoint the differences between pairs of population means that contributed to the rejection of the overall null hypothesis, use
a) Cohen's d.
b) the partial squared curvilinear correlation.
c) a point estimate.
d) Tukey's HSD.
17.18 Use Cohen's d to estimate the effect size for
a) any mean difference.
b) any significant mean difference.
c) the smallest observed mean difference.
d) the largest observed mean difference.
17.19 Except for a new error term, reflecting the absence of variability due to individual differences, analyses involving either repeated or non-repeated (independent) measures are essentially the same with respect to
a) the F ratio.
b) Cohen's d.
c) Tukey’s HSD test.
d) all of the above.
17.20 Given the following ANOVA summary table,
SOURCE SS df MS F
Between 36 3
Within 110 44
Subject 44 11
Error 66 33
Total 146 47
the number of subjects equals
a) 3
b) 11
c) 12
d) 33
17.21 Given the following ANOVA summary table,
SOURCE SS df MS F
Between 36 3
Within 110 44
Subject 44 11
Error 66 33
Total 146 47
the F ratio equals
- 3
b) 4
c) 5
d) 6
17.22 If an investigator erroneously treats each score as though it was contributed by a different subject even though, in fact, scores involve repeated measures, the value of the resulting F test probably would be
a) depressed.
b) inflated.
c) about the same.
d) fairly accurate.
17.23 Repeated-measures ANOVA assumes “sphericity,” that is, the equality of all possible population
a) means.
b) distributions.
c) standard deviations.
d) correlations.
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