Question

There were 50 men and 50 women who were randomly selected from a larger population.
•A t-test was conducted to compare men and women’s performance on an assessment after eating chocolate. The results showed an independent t-test value of t .05(99) = 3.43; p < .05Research Report
Does this mean that the outcome was negative and the percentage of woman who performed better was 5% ?

Answer 1

This means that the difference between men and women was significant, P ≤ .05. There is a 5% probability that this difference is caused solely by chance (alpha error), but scientists tend to assume that chance is not acting in this case.

Why wasn't there a performance assessment on both groups before eating the chocolate to compare the changes?