Final answer:
The assumption of unequal variances is made in an independent samples t-test in Excel because this approach, using the Aspin-Welch t-test, remains valid whether the variances are equal or not. It is a more cautious approach that ensures accurate results under more general conditions.
Step-by-step explanation:
When conducting an independent samples t-test in Excel and assuming unequal variances, we do this because it is safer to not assume equal variances unless we have specific evidence to support it. This approach is reflected in the use of the Aspin-Welch t-test, which is designed for situations where the population standard deviations may be unknown and unequal. The answer to the student's query is that b. The results will still be accurate if the variances are unequal. The t-test is robust to the assumption of equal variances, especially when the sample sizes in the two groups being compared are similar. This is because if the variances happen to be equal, the Aspin-Welch t-test will still yield valid results, and if they are not equal, the test corrects for this by adjusting the degrees of freedom used in the test statistic.
It's important to note that there are two assumptions that must be met to perform an F test of two variances: the populations from which the two samples are drawn are normally distributed, and the two populations are independent of each other.