1. An ANOVA differs from a 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 ttest for independent means cannot be used to compare more than two groups. ' C) is conducted before the experiment, while a ttest for independent means is conducted after the experiment. D) includes computation of group variances as part of the analysis, while a ftest does not include these computations. 2. ANOVA should be conducted only when . (Think about the assumptions we make for ANOVA) sample sizes are greater than 30 per group. sample sizes are smaller than 30 per group. & B C D ~ population variances can be assumed to be equal. population sizes are approximately equal. 3. In an ANOVA, if the within-groups (Error) variance estimate is about the same as the between- groups (Treatment) variance estimate, then A) the null hypothesis should be rejected. B) any difference between sample means is probably due to random sampling error or \"chance factors\" -1 error has been made in computing the between-groups and the within-groups variance ~ C S estimates. any difference between sample means is probably due to a real difference caused by experimental conditions. D S 4. Inan ANOVA, if the null hypothesis is false (you reject the null), 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