Which two results occur when the null hypothesis is accepted using a t-test?

This statement is true; when the null hypothesis is accepted, the t-test statistic must be less than the critical value. This outcome means that the sample means are not significantly different, which is a fundamental aspect of hypothesis testing.

This statement contradicts the premise of accepting the null hypothesis. When the null hypothesis is accepted, it suggests that any observed differences between the two samples are not statistically significant, thus indicating no real difference.

This statement is incorrect as well; if the test statistic were greater than the critical value, the null hypothesis would be rejected. This would imply that there is significant evidence of a difference between the samples, which is the opposite of accepting the null hypothesis.

This statement is accurate and complements the acceptance of the null hypothesis. Accepting the null hypothesis indicates that the data does not provide enough evidence to conclude that a significant difference exists between the two samples.