To compare the dry braking distances from 30 to 0 miles per hour for two makes of automobiles, a safety engineer conducts braking tests for 35 models of Make A and 35 models of Make B. The mean braking distance for Make A is 43 feet. Assume the population standard deviation is 4.7 feet. The mean braking distance for Make B is 45 feet. Assume the population standard deviation is 4.3 feet. At $\alpha=0.10$, can the engineer support the claim that the mean braking distances are different for the two makes of automobiles? Assume the samples are random and independent, and the populations are normally distributed. Complete parts (a) through (e).

Click here to view page 1 of the standard normal distribution table.
Click here to view page 2 of the standard normal distribution table.
C. The mean braking distance is greater for Make A automobiles than Make B automobiles.
D. The mean braking distance is different for the two makes of automobiles.

What are $\mathrm{H}_{0}$ and $\mathrm{H}_{\mathrm{a}}$ ?
A.
\[
\begin{array}{l}
H_{0}: \mu_{1}> \mu_{2} \\
H_{a}: \mu_{1} \leq \mu_{2}
\end{array}
\]
D.
\[
\begin{array}{l}
H_{0}: \mu_{1} \leq \mu_{2} \\
H_{a}: \mu_{1}> \mu_{2}
\end{array}
\]
B.
\[
\begin{array}{l}
H_{0}: \mu_{1}=\mu_{2} \\
H_{a}: \mu_{1} \neq \mu_{2}
\end{array}
\]
E.
\[
\begin{array}{l}
H_{0}: \mu_{1}< \mu_{2} \\
H_{a}: \mu_{1} \geq \mu_{2}
\end{array}
\]
C.
\[
\begin{array}{l}
H_{0}: \mu_{1} \geq \mu_{2} \\
H_{a}: \mu_{1}< \mu_{2}
\end{array}
\]
\[
\text { F. } \begin{array}{l}
H_{0}: \mu_{1} \neq \mu_{2} \\
H_{a}: \mu_{1}=\mu_{2}
\end{array}
\]
(b) Find the critical value(s) and identify the rejection region(s).

The critical value(s) is/are $\square$.
(Round to two decimal places as needed. Use a comma to separate answers as needed.)