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Kavita has been assigned the task of studying the average customer receipt for a branch of a major chain. The average receipt for the chain is [tex]\[tex]$72.00[/tex] with a standard deviation of [tex]\$[/tex]11.00[/tex]. The branch she is studying has an average bill of [tex]\[tex]$67.00[/tex] for the last 40 receipts. She needs to know if this falls below the chain's average at a given level of significance because she does not want to inadvertently report the restaurant's income as lower than it is.

\begin{tabular}{|c|c|c|c|}
\hline \multicolumn{4}{|c|}{Upper-Tail Values} \\
\hline a & $[/tex]5\%[tex]$ & $[/tex]2.5\%[tex]$ & $[/tex]1\%[tex]$ \\
\hline \begin{tabular}{c}
Critical \\
$[/tex]z$-values
\end{tabular} & 1.65 & 1.96 & 2.58 \\
\hline \hline
\end{tabular}

Which choice depicts the result for Kavita's hypothesis test?

A. She should reject [tex]H_0: \mu = 72[/tex] and accept [tex]H_a: \mu \ \textless \ 72[/tex].

B. She should reject [tex]H_0: \mu = 72[/tex] and accept [tex]H_a: \mu \neq 72[/tex].

C. She should accept [tex]H_0: \mu = 72[/tex] and reject [tex]H_a: \mu \neq 72[/tex].

D. She should reject [tex]H_a: \mu \ \textless \ 72[/tex] but cannot accept [tex]H_0: \mu = 72[/tex].

Sagot :

To address Kavita's hypothesis test, we need to follow these steps:

1. Define the hypotheses:
- Null hypothesis ([tex]\(H_0\)[/tex]): The average receipt for the branch is the same as the chain's average: [tex]\( \mu = 72 \)[/tex].
- Alternative hypothesis ([tex]\(H_a\)[/tex]): The average receipt for the branch is less than the chain's average: [tex]\( \mu < 72 \)[/tex].

2. Identify the significance level:
- Given in the problem is a significance level ([tex]\( \alpha \)[/tex]) of [tex]\(0.05\)[/tex] or [tex]\(5\%\)[/tex].

3. Calculate the test statistic (z-score):
- Using the sample size ([tex]\( n = 40 \)[/tex]), the chain's mean ([tex]\( \mu = 72 \)[/tex]), the branch's mean ([tex]\( \bar{x} = 67 \)[/tex]), and the chain's standard deviation ([tex]\( \sigma = 11 \)[/tex]), we use the formula for the z-score:
[tex]\[ z = \frac{\bar{x} - \mu}{\frac{\sigma}{\sqrt{n}}} \][/tex]
- Plugging in the numbers:
[tex]\[ z = \frac{67 - 72}{\frac{11}{\sqrt{40}}} = \frac{-5}{\frac{11}{6.3246}} \approx -2.875 \][/tex]
Thus, the z-score is approximately [tex]\(-2.875\)[/tex].

4. Determine the critical z-value:
- For a one-tailed test at [tex]\( 0.05 \)[/tex] significance level, the critical z-value is [tex]\(-1.65\)[/tex] (negative because it is a lower-tail test).

5. Compare the test statistic to the critical value:
- The calculated z-score ([tex]\(-2.875\)[/tex]) is less than the critical z-value ([tex]\(-1.65\)[/tex]).

6. Make a decision:
- Since [tex]\(-2.875 < -1.65\)[/tex], we reject the null hypothesis ([tex]\(H_0\)[/tex]).

Thus, the test statistic falls into the rejection region, indicating that there is sufficient evidence to reject the null hypothesis in favor of the alternative hypothesis. The result is significant at the [tex]\(5\%\)[/tex] level, suggesting that the average receipt at the branch is indeed less than the chain's average.

Therefore, the correct choice is:
- She should reject [tex]\( H _0: \mu=72 \)[/tex] and accept [tex]\( H _{ a }: \mu<72 \)[/tex].
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