Questions: The TTC has set a bus mechanical reliability goal of 3,900 bus miles. Bus mechanical reliability is measured specifically as the number of bus miles between mechanical road calls. Suppose a sample of 100 buses resulted in a sample mean of 3,950 bus miles and a sample standard deviation of 175 bus miles. Complete parts (a) and (b) below.
a. Is there evidence that the population mean bus miles is more than 3,900 bus miles? (Use a 0.05 level of significance.) State the null and alternative hypotheses.
H0: μ = T
H1: μ ≠ T
(Type integers)
Find the test statistic for this hypothesis test.
The test statistic t= (Round to two decimal places as needed.)
The critical value for the test statistic is(are) .
(Round to two decimal places as needed)
Is there sufficient evidence to reject the null hypothesis using α=0.05 ?
A. Do not reject the null hypothesis. There is insufficient evidence at the 0.05 level of significance that the population mean bus miles is less than 3,900 bus miles.
B. Reject the null hypothesis. There is sufficient evidence at the 0.05 level of significance that the population mean bus miles is greater than 3,900 bus miles.
C. Reject the null hypothesis. There is sufficient evidence at the 0.05 level of significance that the population mean bus miles is less than 3,900 bus miles.
D. Do not reject the null hypothesis. There is insufficient evidence at the 0.05 level of significance that the population mean bus miles is greater than 3,900 bus miles.
b. The p-value is . (Round to 3 decimal places as needed.)
What does this p-value mean given the results of part (a)?
A. The p-value is the probability of getting a sample mean of 3,950 bus miles or greater if the actual mean is 3,900 bus miles.
B. The p-value is the probability that the actual mean is 3,950 bus miles or less.
C. The p-value is the probability that the actual mean is 3,900 bus miles or greater given the sample mean is 3,950 bus miles.
Transcript text: The TTC has set a bus mechanical reliability goal of 3,900 bus miles. Bus mechanical reliability is measured specifically as the number of bus miles between mechanical road calls. Suppose a sample of 100 buses resulted in a sample mean of 3,950 bus miles and a sample standard deviation of 175 bus miles. Complete parts (a) and (b) below.
a. Is there evidence that the population mean bus miles is more than 3,900 bus miles? (Use a 0.05 level of significance.) State the null and alternative hypotheses.
\[
\begin{array}{l}
\mathrm{H}_{0}: \mu \square \mathbf{T} \\
\mathrm{H}_{1}: \mu \square \mathbf{T}
\end{array}
\]
(Type integers)
Find the test statistic for this hypothesis test.
The test statistic $\mathrm{t}=$ $\square$ (Round to two decimal places as needed.)
The critical value for the test statistic is(are) $\square$ .
(Round to two decimal places as needed)
Is there sufficient evidence to reject the null hypothesis using $\alpha=0.05$ ?
A. Do not reject the null hypothesis. There is insufficient evidence at the 0.05 level of significance that the population mean bus miles is less than 3,900 bus miles.
B. Reject the null hypothesis. There is sufficient evidence at the 0.05 level of significance that the population mean bus miles is greater than 3,900 bus miles.
C. Reject the null hypothesis. There is sufficient evidence at the 0.05 level of significance that the population mean bus miles is less than 3,900 bus miles.
D. Do not reject the null hypothesis. There is insufficient evidence at the 0.05 level of significance that the population mean bus miles is greater than 3,900 bus miles.
b. The p-value is $\square$ . (Round to 3 decimal places as needed.)
What does this p-value mean given the results of part (a)?
A. The p-value is the probability of getting a sample mean of 3,950 bus miles or greater if the actual mean is 3,900 bus miles.
B. The p-value is the probability that the actual mean is 3,950 bus miles or less.
C. The $\rho$-value is the probability that the actual mean is 3,900 bus miles or greater given the sample mean is 3,950 bus miles.
Solution
Solution Steps
Step 1: Standard Error Calculation
The standard error \( SE \) is calculated using the formula:
\[
SE = \frac{\sigma}{\sqrt{n}} = \frac{175}{\sqrt{100}} = 17.5
\]
Step 2: Test Statistic Calculation
The test statistic \( Z_{test} \) is calculated as follows:
\[
Z_{test} = \frac{\bar{x} - \mu_0}{SE} = \frac{3950 - 3900}{17.5} = 2.8571
\]
Step 3: P-value Calculation
For a right-tailed test, the p-value is calculated as:
\[
P = 1 - T(z) = 0.0021
\]
Step 4: Critical Value Determination
The critical value for a right-tailed test at a significance level of \( \alpha = 0.05 \) with \( n - 1 = 99 \) degrees of freedom is:
\[
\text{Critical Value} \approx 1.6604
\]
Step 5: Decision on the Null Hypothesis
Since the test statistic \( Z_{test} = 2.8571 \) is greater than the critical value \( 1.6604 \), we reject the null hypothesis. Thus, there is sufficient evidence at the \( 0.05 \) level of significance that the population mean bus miles is greater than \( 3900 \).
Step 6: Interpretation of the P-value
The p-value \( 0.0021 \) indicates the probability of obtaining a sample mean of \( 3950 \) bus miles or greater if the actual mean is \( 3900 \).
Final Answer
The answer is \( \boxed{B} \). The p-value interpretation is \( \boxed{A} \).