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Lucille is interested in the effects of alcohol consumption on style of play while playing the video game Sims.She asks a group of 15 college students to play Sims under one of the following conditions: no alcohol, 1 ounce of alcohol, 2 ounces of alcohol, or 3 ounces of alcohol.Lucille measures on a scale of 1 to 10 how prosocial the students' style of play is.After collecting the data, Lucille performs an ANOVA and finds that she can reject the null hypothesis.On this basis, what does Lucille know?


A) She knows that greater levels of alcohol consumption are associated with a more prosocial style of play.
B) She knows that there is a difference among the groups somewhere, but she does not know where.
C) She knows that moderate alcohol consumption is associated with prosocial play, but that greater alcohol consumption is associated with an antisocial style of play.
D) She knows that drinking any amount of alcohol affects the style of play.

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The z, t, and F distributions have something in common-the numerator of the test statistic:


A) contains a measure of difference among group means.
B) contains a measure of difference within the various groups.
C) is a squared number.
D) represents what would be expected to happen by chance.

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The values observed on the F table under two samples are the same as those on the t table.

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Within-groups degrees of freedom is calculated by:


A) subtracting 1 from the total number of groups in the study.
B) multiplying the number of subjects by the number of conditions in the study and then subtracting 1.
C) subtracting 1 from the total number of subjects in the study.
D) for each condition, subtracting 1 from the number of subjects in that group and then adding together the totals for all the groups.

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When computing Tukey HSD with samples of different sizes, what additional step must be performed?


A) Calculate a weighted sample size called a harmonic mean.
B) Calculate HSD for each pair of means.
C) Compare the means of all groups using Bonferroni first.
D) Compute R2.

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A measure of the differences among group means is:


A) the z score.
B) between-groups variance.
C) within-groups variance.
D) the proportionate reduction in error.

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A researcher rejects the null hypothesis after using an F table to determine the significance value.What can be concluded?


A) There is a difference between means that we expected just by chance.
B) There is a difference between means that is larger than we would predict by chance.
C) There is no difference between means, which is what we would expect by chance.
D) There is no difference between means.

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The F statistic increases when:


A) within-groups variance decreases.
B) between-groups variance decreases.
C) between-groups variance increases.
D) within-groups variance decreases and between-groups variance increases.

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As the number of t tests increases, the risk of a Type I error decreases.

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When the null hypothesis is true, the F ratio for analysis of variance is expected, on average, to be 1.

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In which situation would it be necessary to use a between-groups ANOVA?


A) A researcher is interested in a longitudinal study that follows a group of kindergarten children through high school and assesses their body mass index at four time points.
B) A researcher classifies a group of college students on the basis of their political leanings as liberal, conservative, libertarian, or green.
C) A researcher is interested in the effects of distraction on driving performance and randomly assigns participants to one of three distraction groups.
D) A researcher is interested in whether a sensitivity training class changes attitudes toward minority populations.The researcher assesses these attitudes before and after the sensitivity training class.

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MSwithin is obtained by dividing:


A) SSbetween by dfbetween.
B) SSbetween by SSwithin.
C) dfbetween by SSwithin.
D) SSwithin by dfwithin.

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With two groups, the square root of F is equal to:


A) t.
B) 0.0.
C) 1.0.
D) 2t.

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The values observed on the F table under two samples is the square of those on the t table.

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If the p level is.0.05 and the null hypothesis is true, what is the probability of NOT making a Type I error (i.e., one will correctly fail to reject the null hypothesis) ?


A) 0.05
B) 0.90
C) 0.95
D) 0.00

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There is a different F distribution for every:


A) sample size.
B) level of the independent variable.
C) combination of sample size and number of samples.
D) within-groups degrees of freedom.

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Does the F distribution take into account individual differences when comparing sample means?


A) No; we should be careful not to generalize the results because the error of the F statistic is very large.
B) No; that is why we should only rarely use the F distribution and instead run multiple t tests.
C) Yes; as the variability within the individual samples decreases, the F statistic becomes larger since the distributions are not overlapping very much.
D) Yes; as the variability within the individual samples decreases, the F statistic becomes smaller and less confident.

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F is obtained by dividing _____ by _____.


A) SSbetween; dfbetween
B) MSbetween; MSwithin
C) dfbetween; SSbetween
D) SSbetween; SSwithin

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If an F statistic is negative, which of these is true?


A) The within-groups variance exceeds the between-groups variance.
B) The difference among the group means is greater than what would have occurred by chance.
C) There has been a calculation error.
D) The difference among the group means is less than what would have occurred by chance.

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A one-way ANOVA includes:


A) one nominal dependent variable with more than two levels and a scale independent variable.
B) one nominal independent variable with more than two levels and a scale dependent variable.
C) one nominal dependent variable with more than three levels and a scale independent variable.
D) one nominal independent variable with more than three levels and a scale dependent variable.

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