Question

Please keep in mind that this example is just made up and does not represent any actual findings! The verdict is still out and researchers do not know whether there is an effect for gender.)

A researcher is analyzing a dataset that include individuals who have tested positive for COVID-19. He is especially interested in testing whether men and women are equally likely to get infected. He runs a chi-square goodness of fit test to test his hypotheses.

The chi-square test is not significant, p > .05. What is the right conclusion?

		He should not reject H0. The same amount of men and women in the dataset have tested positive.
		He should not reject H0. The amount of men and women who have tested positive differs.
		He should accept H1. The amount of men and women who have tested positive differs.
		He should accept H1. The same amount of men and women in the dataset have tested positive.

Answer 1

He should not reject H0. The same amount of men and women in the dataset have tested positive.

Explanation:

For the given Chi-square goodness-of-fit test, the null and alternative hypotheses are given as below:

Null hypothesis: H₀: The men and women are equally likely to get infected.

Alternative hypothesis: H_a: The men and women are not equally likely to get infected.

The chi-square test is not significant, that is, p-value is greater than alpha value 0.05, so we do not reject the null hypothesis that the men and women are equally likely to get infected. The same amount of men and women in the dataset has tested positive.