54 Questions
What is the purpose of partitioning variability in ANOVA?
To separate variability into different components
What type of variability is calculated by summing up the variability of each subject around their own mean?
Within-subjects variability
What is the purpose of experimental manipulation in ANOVA?
To introduce a treatment effect
What is the difference between treatment variability and error variability?
Treatment variability is due to the experimental manipulation, while error variability is due to random fluctuations
What is the purpose of the repeated-measures ANOVA?
To partition variability into treatment and error components
What are SSmodel and SSresidual adjusted by in the repeated-measures ANOVA?
The degrees of freedom
What is the primary goal of partitioning variability in ANOVA?
To separate the variability into within-group and between-group components
What type of variability is accounted for in the error term in repeated-measures ANOVA?
Within-subjects variability
What is the primary source of variability in the experimental manipulation?
Treatment effects
What is the main difference between within-subjects variability and between-subjects variability?
One is used for repeated-measures ANOVA and the other is used for between-subjects ANOVA
Why is it important to separate the variability into within-group and between-group components in ANOVA?
To identify the sources of variability and estimate the treatment effects
What is the main advantage of using repeated-measures ANOVA?
It can control for individual differences in performance
What is the main purpose of using a repeated-measures design in an experiment?
To reduce the impact of individual differences on the results
What is the primary source of variability that is 'cancelled out' in a repeated-measures design?
Variance created by individual differences
What is the benefit of using a repeated-measures design in terms of error variance?
It reduces the error variance
What is the main disadvantage of using a repeated-measures design?
It is prone to fatigue and learning effects
What is the research question being addressed in the example experiment?
What is the effect of weather on problem solving?
What is the statistical test used to analyze the data in the example experiment?
One-way repeated-measures ANOVA
What is the primary purpose of the Bonferroni correction in post-hoc tests?
To reduce the familywise error rate
What is the main difference between the Holm's and Hochberg's tests in sequential post-hoc analysis?
The order of testing significance
What is the Friedman test used for in non-parametric ANOVA alternatives?
Comparing multiple groups with repeated measures
What is the main disadvantage of non-parametric tests, such as the Kruskal-Wallis test?
They are developed for a limited range of situations
What is the purpose of calculating ranks in the Friedman test?
To calculate the mean ranks per treatment
What is the primary purpose of bootstrapping in non-parametric ANOVA alternatives?
To estimate the confidence intervals
What is the main drawback of using non-parametric tests, such as the Kruskal-Wallis test, compared to their parametric counterparts?
They are less powerful and may lose information about the magnitude of differences.
What is the purpose of ranking the data in the Kruskal-Wallis test?
To allow for the calculation of the H statistic.
Which of the following is a non-parametric alternative to the one-way repeated-measures ANOVA?
Friedman test.
Why are direct tests of normality, such as the Shapiro-Wilk test, not recommended?
They have a high false positive rate for larger samples and low power for smaller samples.
What is the advantage of using the Kruskal-Wallis test instead of the one-way ANOVA when the data is not normally distributed?
It is more robust to outliers and non-normality.
What is the purpose of the H statistic in the Kruskal-Wallis test?
To compare the sums of ranks between groups.
What is the primary advantage of using the Kruskal-Wallis test over traditional ANOVA?
It is more robust to deviations from normality
What is the main difference between the Kruskal-Wallis test and the Friedman test?
The Kruskal-Wallis test is used for between-subjects designs, while the Friedman test is used for within-subjects designs
What is the primary purpose of using rank-based statistical analysis?
To accommodate non-normal data
What is the purpose of using post-hoc tests with Bonferroni correction?
To reduce the Type I error rate
What is the primary limitation of non-parametric ANOVA alternatives?
They are less powerful than parametric tests
What is the primary advantage of using resampling methods?
They are more robust to deviations from normality
What is the primary limitation of direct tests of normality, such as the Kolmogorov-Smirnov test?
High false positive rate for larger samples and low power for smaller samples.
What is the purpose of calculating skewness and kurtosis in statistical analysis?
To test for normality of the data.
What is the advantage of using the Kruskal-Wallis test over traditional ANOVA when the data is not normally distributed?
It is less sensitive to deviations from normality.
What is the purpose of interpreting the standard error in statistical analysis?
To determine the significance of the results.
What is the primary advantage of using non-parametric tests, such as the Kruskal-Wallis test?
They are less sensitive to deviations from normality.
What is the primary limitation of non-parametric tests, such as the Kruskal-Wallis test, compared to their parametric counterparts?
They are less powerful than parametric tests.
What is the underlying assumption that is being addressed by using a Bonferroni correction in pairwise comparison?
Homogeneity of variance
What is the primary advantage of using the Friedman test over the Kruskal-Wallis test?
It is suitable for repeated-measures designs
What is the consequence of violating the assumption of homogeneity of variance in ANOVA?
Increased risk of Type I errors
What is the purpose of bootstrapping in non-parametric ANOVA alternatives?
To generate confidence intervals for the treatment effect
Why are non-parametric tests, such as the Kruskal-Wallis test, preferred over traditional ANOVA when the data is not normally distributed?
They are more robust to non-normality
What is the primary limitation of using sequential methods, such as Holm's and Hochberg's tests, in post-hoc analysis?
They are too conservative and result in low power
What is the consequence of having unequal sample sizes in between-subjects ANOVA?
F-ratio becomes more conservative
What is the rule of thumb for sample size in normality testing?
≥ 30
What is the purpose of checking for skewness and kurtosis in normality testing?
To determine if the data is normally distributed
What is the consequence of violating the assumption of homogeneity of variance in ANOVA?
F-ratio becomes more liberal
What is the purpose of Levine's test in ANOVA?
To check for homogeneity of variance
What is the central limit theorem related to in normality testing?
Sampling distribution of the parameter
This quiz covers the concept of partitioning variability in analysis of variance (ANOVA) for both between-subjects and repeated measures designs.
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