Analyses were run. The following is the (edited) output for the test:
Hypothesis test results:
U1: favored team-home game
U2: favored team- away game
Difference Sample Mean Std. Err. DF T-Stat P-value
U1-U2 .11 0.67168534 94.155815 0.16376716 0.4351
From the output we learn that:
A. the data provide sufficient evidence reject the H0; thus, we cannot conclude that the
mean point spread of home games is higher than that of away games.
B. the data do not provide sufficient evidence reject the H0; thus, we can conclude that
the mean point spread for home games is higher than that of away games.
C. the data do not provide sufficient evidence to reject H0; thus, we cannot conclude that
the mean point spread of home games is higher than that of away games.
D. the data provide sufficient evidence to reject H0; thus, we can conclude that the mean
point spread for home games is higher than that of away games.

Respuesta :

Answer: C. The data do not provide sufficient evidence to reject H0; thus, we cannot conclude that the mean point spread fo home games is higher than that of away games.

Step-by-step explanation: In Hypothesis Testing using p-value, after stating the null an alternative hypothesis, you have to compare p-value with level of significance, also known as α. If p-value is less than α, reject null hypothesis and accept alternative. If p-value is bigger, we would fail to reject null hypothesis and not accept the alternative.

In the above testing, P-value is 0.4351. Level of significance is, generally, 0.05. Comparing them, p-value is bigger than α. What it means is there is not enough evidence to support null hypothesis and, consequently, we can't conclude the difference in mean point spread of home games is higher than of the away games.

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