Answer:
The right options are C and D.
Step-by-step explanation:
One test refers to the claim that there is bias in the acceptance rate based on gender. In this case, the alternative hypothesis would claim that there is a significant difference in proportions in acceptance rate for both genders. The null hypothesis failed to be rejected, so the P-value has to be more than the significance level.
<em>C. One set of hypotheses concerns whether acceptance rates are lower (the alternative) or equivalent (the null) when the author or editor is female. The p-value for that test was apparently above 0.05.</em>
The other test is referred to the preference in gender to choose reviewers. The alternative hypothesis claim that female editors used female reviewers more often than did male editors. This has a P-value<0.001.
<em>D. One set of hypotheses concerns whether female editors chose females to review the papers less often than the alternative) or the same amount as the null) did male editors. The p-value for that test was reported to be less than 0.001.</em>
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