If an experimenter conducts a t test for independent means and rejects the null hypothesis, the correct interpretation is that:
a. the variance of one sample is so much larger than the variance of the other sample that the variances of the parent populations must not have been the same after all b. the mean of one sample is statistically the same as the mean of the other sample, so they probably come from populations with equal means c. the samples were from populations that were actually dependent rather than independent d. the mean of one sample is so far from the mean of the other sample that the samples must come from populations with different means
Rejecting the null hypothesis means we've found a significant difference in the means. That means the probability that we'd see means so far apart by chance is less than our threshold of significance.
