A university administrator was interested in determining if there was a difference in the distance students travel to get from class from their current residence(in miles). Men and women at UF were randomly selected. The Minitab output is below. What is the best interpretation for the output? Difference = mu (F) - mu (M) T-Test of difference = 0 (vs not =): T-Value = -1.05 P-Value = 0.305 DF = 21

2) We do not have sufficient evidence to support the claim that the mean distance students traveled to school from their current residence was different for males and females.

Step-by-step explanation:

A university administrator wants to test if there is a difference between the distance men and women travel to class from their current residence. So, the hypothesis would be:

[tex]H_{o}: \mu_{F}-\mu_{M}=0\\\\ H_{a}: \mu_{F}-\mu_{M}\neq 0[/tex]

The results of his tests are:

t-value = -1.05

p-value = 0.305

Degrees of freedom = df = 21

Based on this data we need to draw a conclusion about test. The significance level is not given, but the normally used levels of significance are 0.001, 0.005, 0.01 and 0.05

The rule of the thumb is:

If p-value is equal to or less than the significance level, then we reject the null hypothesis
If p-value is greater than the significance level, we fail to reject the null hypothesis.

No matter which significance level is used from the above mentioned significance levels, p-value will always be larger than it. Therefore, we fail to reject the null hypothesis.

Conclusion:

We do not have sufficient evidence to support the claim that the mean distance students traveled to school from their current residence was different for males and females.