ANOVA Flashcards
LEAN ANOVANOVA
1) An analysis of variance differs from a t test for independent means in that an analysis of variance
A) is usually used to compare two groups, while a t test for independent means can be used to compare two or more groups.
B) can be used to compare three or more groups, while a t test for independent means cannot be used to compare more than two groups.
C) is conducted before the experiment, while a t test for independent means is conducted after the experiment.
D) Includes the computation of a pooled error term as part of the analysis, while a t test does not use a pooled error term.
B - ANOVA compares the means of different groups whether through BG or WG. While t-tests can only compare two means. Comparing with the t-test multiple times would increase the type 1 error.
2) Because of the assumption that the population variances are equal, when conducting an analysis of variance
A) fewer degrees of freedom are required.
B) sample variances are not important.
C) an average estimate of the population variance is computed.
D) population parameters are used instead of sample statistics.
It is C. Probably important.
3) In an analysis of variance, if the null hypothesis is true, then
A) the research hypothesis can also be true.
B) fewer participants can be included in the experiment.
C) there is less variance among means of samples than if the null hypothesis were not true.
D) the within-groups estimate of the population variance is smaller than the between-groups estimate.
Answer is C. Essentially if the alternative hypothesis (H1) was true then the Fobserved > Fcritical indicating a significant difference between the means.
4) In a one-way analysis of variance, if the null hypothesis is true, then
A) the analysis of variance can never produce a significant F ratio.
B) estimates of the population variance will be easier to figure.
C) the variance between sample means will be larger than the variance within each sample.
D) any difference among sample means reflects variance within the populations.
The answer is D. I didn’t know this.
5) In an analysis of variance, if the within-groups variance estimate is about the same as the between-groups variance estimate, then
A) the null hypothesis should be rejected.
B) any difference between sample means is probably due to random sampling error.
C) an error has been made in computing the between-groups and the within-groups variance estimates.
D) any difference between sample means is probably due to a real difference caused by experimental conditions.
B - any difference between sample means is probably due to random sampling error. ??
6) In an analysis of variance, if the null hypothesis is false, then
A) the variation between sample means reflects the variation within the populations as well as the variation between the population means.
B) the within-groups variance is significantly larger than the between-groups variance.
C) the variance within each sample is larger than if the null hypothesis were true.
D) the variance between sample means is no greater than the variance within the population with the largest variance.
A
7) In an analysis of variance, the null hypothesis will be retained when the F ratio is A) negative. B) Significantly larger than 1. C) equal to the t score. D) Close to 1.
Close to 1. Tricky. Alternative hypothesis will be larger than 1. Where the null would be close.
8) “MSWithin” equals
A) the sum of squares within each group.
B) the square root of the standard within-groups deviations from the mean.
C) the squared variance within groups.
D) the population variance estimate based on the variation of participant scores around their condition or group mean.
D
9) Joe conducts an analysis of variance. If he rejected the null hypothesis, the most likely F value of those below is A) 0.64 B) 1.01 C) 3.57 D) –5.12
Hey this is tricky one. You know that Sig F = above 1. Therefore it will be 3.57.
10) The formula “Σn(M–GM)2/dfBetween” is used to compute
A) the F ratio for a repeated measures design.
B) the between-groups sum of squared deviations.
C) the estimated variance of the distribution of means.
D) the between-groups estimate of the population variance.
oh snap. D. This is tricky one. Because It can also be (S2m)(N) - with s2m = Σ(M- GM)2 / dfBetween - dfBetween = Ngroups - 1.
13) A characteristic of an F ratio is that
A) the cutoff F equals the calculated F divided by 2.
B) it can never be less than 0.
C) it is negatively skewed.
D) the t distribution for ∞ df is the comparison distribution.
B - it can never be less than 0.
14) Ann conducts a study, and finds that the estimated population variances for the 4 groups in her study are 12.8, 16.3, 15.1, and 19.9. What is the within-groups estimate of the population variance?
A) (12.82 + 16.32 + 15.12 + 19.92) / (4 – 1) = 351.18.
B) (12.82 + 16.32 + 15.12 + 19.92) / 4 = 263.39.
C) (12.8 + 16.3 + 15.1 + 19.9) / (4 – 1) = 21.37.
D) (12.8 + 16.3 + 15.1 + 19.9) / 4 = 16.03.
It is D - S2within = S21 + S22 + … + S2Last / Ngroups
15) The overall test of the significance of the difference among groups in an analysis of variance is called A) an omnibus test. B) a planned comparison. C) an absolute contrast. D) a post-hoc test.
Omnibus
16) A planned comparison comparing two means involves figuring an F ratio in which the numerator
A) depends on which pair of means is being compared.
B) has exactly 2 degrees of freedom.
C) is the overall between-groups population variance estimate, regardless of the pair of means being compared.
D) does not involve figuring an F ratio for any planned comparison.
(A) - this might be important.
17) Which statistical procedure ensures that the alpha level for any given planned contrast will not exceed .05? A) Tukey B) Scheffé C) Bonferroni D) Gosset
Bonferroni
