Deck 13: Analysis of Variance Anova
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Deck 13: Analysis of Variance Anova
1
Analysis of variance is used to test the equality of means across three or more categories.
True
2
The global F-test tests whether all groups have significantly different means.
False
3
A post hoc test tests all possible pairs of mean differences.
True
4
Tukey, Bonferroni, and Scheffe are the names of three popular t-tests.
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5
Analysis of variance is not appropriate for testing the statistical significance of continuous ordinal variable relationships.
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6
Analysis of variance appears to be less robust than the t-test for deviations from normality.
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7
Our main concern with homogeneity is that there are no substantial differences in the amount of variance across the groups.
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8
The Levene's test is a test for testing whether variances across groups are equal.
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9
The term "homogeneous subsets" means that groups that have statistically identical means.
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10
The Levene's test is a test for testing whether changes in means are linear.
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11
Multiple analysis of variance involves the analysis of more than one independent variable on a single dependent variable.
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12
An interaction effect between two variables describes the way that variables "work together" to have an effect on the dependent variable.
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13
Two-way analysis of variance, for example, allows for testing of the effect of two different independent variables on the dependent variable.
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14
A nonparametric alternative to one-way analysis of variance (ANOVA) is Kruskal-Wallis' H test of one-way ANOVA.
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15
Kruskal-Wallis' H test reports mean values of the dependent variable and identifies heterogeneous subsets.
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