How does an ANOVA differ from a t test of independent samples?

Question

1. An ANOVA allows the comparison of mean scores between and among two or more groups. This test notes that a difference is found, if there is one, but not where the difference lies.
2. An ANOVA is a much higher level test and has no comparison to a t test.
3. An ANOVA compares the means of two or more groups on the dependent measure but an independent t test compares pre- and post scores.
4. An ANOVA gives the reader information about the population of interest but not about the sample in a particular study.

Answer 1

1
Rationale 1: ANOVAs and t test for independent samples are very similar, but if you calculated the multiple t test within the same sample, you would be increasing the chance of a false positive or type I error. ANOVAs can only be one-tailed since the test notes whether or not there is a difference, but not where that difference lies if there are more than two groups.
Rationale 2: Both ANOVA and independent sample t test are parametric statistics.
Rationale 3: Do not confuse independent and dependent t tests.
Rationale 4: An ANOVA is a statistic; statistics relate to the sample and from that information one can infer or draw inference about the population of interest.