Final answer:
When looking at statistical measurements, a value of $1 or less indicates a small difference between groups. The p-value and effect size provide additional information about the magnitude of the difference.
Step-by-step explanation:
When looking at the differences in the statistical measurements of group A and group B, a value of $1 or less indicates a small difference. It means that the two groups are very similar in terms of the statistical measurements being compared. For example, if we are comparing the mean grades among sororities and we find that the difference is $1 or less, it suggests that the mean grades are very close for the different sororities.
In statistical hypothesis testing, a p-value is used to determine the significance of a difference. A p-value of 0.0077 indicates that there is strong evidence to suggest a significant difference between group A and group B. The difference is unlikely to have occurred by chance alone. So in this case, the difference is not $1 or less.
The effect size of 0.625 is considered a medium effect size according to Cohen's standard. This indicates a moderate difference between the groups. However, without additional context, it is not possible to determine if the difference is $1 or less.