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A researcher reports t(24) = 5.30 for an independent-measures experiment. How many individuals participated in the entire experiment?
For an independent-measures research study, the value of Cohen's d or r2 helps to describe
how much difference there is between the two treatments
In general, if the variance of the difference scores increases, then the value of the t statistic
will decrease (move toward 0 at the center of the distribution)
A research report describing the results from a repeated-measures study states the data show no significant difference between the two treatments, t(10) = 1.65, p > .05. Based on this report, you can conclude that a total of ________ individuals participated in the research study.
Compared to an independent-measures design, a repeated-measured study is more likely to find a significant effect because it reduces the contribution of variance due to
A researcher uses a repeated-measures study to compare two treatment conditions with a set of 20 scores in each treatment. What would be the value of df for the repeated-measures t statistic?
If the null hypothesis is true and there is no treatment effect, what value is expected on average for the F-ratio?
A researcher reports an F-ratio with df = 2, 36 for an independent-measures experiment. How many treatment conditions were compared in this experiment?
A researcher reports an F-ratio with df = 1, 24 for an independent-measures experiment. How many individual subjects participated in the experiment?
For an experiment comparing more than two treatment conditions you should use analysis of variance rather than separate t tests because
conducting several t tests would inflate the risk of a Type I error
In general the distribution of F-ratios is
positively skewed with all values greater than or equal to zero
A researcher obtains an F-ratio with df = 2, 12 from an ANOVA for a repeated-measures research study. How many subjects participated in the research study?
The results of a repeated-measures ANOVA are reported as follows, F(3, 27) = 1.12, p > .05. How many subjects participated in the study?
extreme sample values that are very unlikely to be obtained if the null hypothesis is true
the probability that the hypothesis test will reject the null hypothesis when there actually is a treatment effect (that it will correctly see the effect)
homogeneity of variance
an assumption that two populations have equal variances (for t tests with independent samples)
η2 (eta squared)
a measure of effect size based on the percentage of variance accounted for by the sample mean differences (similar to r2 but used in ANOVA)
between-treatments SS, df, MS
values used to measure the differences between treatments (mean differences; used in ANOVA)
within-treatments SS, df, MS
values used to measure the differences inside treatment conditions; assumed to measure chance or error variability
differences from one treatment to another; a measure of mean differences (repeated-measures ANOVA)
total number of scores in the entire study (when all the samples are the same size, N = kn) (ANOVA)
when estimation is used
after a hypothesis test where H0 is rejected; when you know an effect is present; to obtain basic information
denominator of the F-ratio (ANOVA); a measure of the variance due to random, unsystematic differences
experimentwise alpha level
overall probability of a Type I over a series of separate hypothesis tests
post hoc tests
additional hypothesis tests done after an ANOVA to determine which mean differences are significant
residual variance (error variance)
how much variance is expected if there are no systematic treatment effects and no individual differences contributing to the variability of the scores
main advantage of repeated-measures ANOVA
elimination of variability caused by individual differences
sample variance is _______ correlated with the likelihood of rejecting the null hypothesis
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