When the null hypothesis is rejected in ANOVA, the ANOVA test reveals which means are significantly different from which other means.

false
True
true
False
Rejecting the null hypothesis only indicates that at least one population mean is different from at least one other.
A marginal mean is

false
A mean that is almost significant.
true
The mean of the means of one variable averaging over the levels of another variable.
The mean of the means of one variable averaging over the levels of another variable.
A main effect is a comparison of

true
Marginal means
false
Standardized means
false
Simple effects
Marginal means
To compare a control group with the average of the other three groups, you would use

false
Tukey's test
false
An interaction test
true
A specific comparison
A specific comparison
To compare each mean with each other mean, you would use

true
Tukey's test
false
An interaction test
false
A specific comparison
false
ANOVA
Tukey's test
An interaction makes it difficult to interpret

false
simple effects
false
pairwise comparisons
false
specific comparisons
true
main effects
Main effects. The interaction means the simple effects differ and therefore the main effect does not tell the whole story.
If one simple effect is significant and another is not, that means there is an interaction.

false
True
true
False
False, because it is not valid to accept the null hypothesis that a simple effect is 0 when it is not significant.