Questions: Decide whether the normal sampling distribution can be used. If it can be used, test the claim about the population proportion p at the given level of significance α using the given sample statistics.
Claim: p ≠ 0.21 ; α=0.01; Sample statistics: p̂=0.15, n=160
Can the normal sampling distribution be used?
A. No, because nq is less than 5.
B. Yes, because both np and nq are greater than or equal to 5.
C. Yes, because pq is greater than α=0.01.
D. No, because np is less than 5.
State the null and alternative hypotheses.
A. H0: p=0.21 Ha: p ≠ 0.21
B. H0: p ≤ 0.21 Ha: p>0.21
C. H0: p ≥ 0.21 Ha: p<0.21
D. The test cannot be performed.
Determine the critical value(s). Select the correct choice below and, if necessary, fill in the answer box to complete your choice.
A. The critical value(s) is/are .
(Round to two decimal places as needed. Use a comma to separate answers as needed.)
B. The test cannot be performed.
Transcript text: Decide whether the normal sampling distribution can be used. If it can be used, test the claim about the population proportion p at the given level of significance $\alpha$ using the given sample statistics.
Claim: $p \neq 0.21 ; \alpha=0.01$; Sample statistics: $\hat{p}=0.15, n=160$
Can the normal sampling distribution be used?
A. No, because $n q$ is less than 5 .
B. Yes, because both np and nq are greater than or equal to 5 .
C. Yes, because pq is greater than $\alpha=0.01$.
D. No, because np is less than 5 .
State the null and alternative hypotheses.
A. $H_{0}: p=0.21$ $H_{a}: p \neq 0.21$
B. $H_{0}: p \leq 0.21$
\[
H_{a}: p>0.21
\]
C. $H_{0}: p \geq 0.21$
\[
H_{a}: p<0.21
\]
D. The test cannot be performed.
Determine the critical value(s). Select the correct choice below and, if necessary, fill in the answer box to complete your choice.
A. The critical value(s) is/are $\square$ .
(Round to two decimal places as needed. Use a comma to separate answers as needed.)
B. The test cannot be performed.
Solution
Solution Steps
Step 1: Normal Sampling Distribution Check
To determine if the normal sampling distribution can be used, we calculate \( np \) and \( nq \):
\[
np = n \cdot p = 160 \cdot 0.21 = 33.6
\]
\[
nq = n \cdot (1 - p) = 160 \cdot 0.79 = 126.4
\]
Since both \( np \) and \( nq \) are greater than or equal to 5, we conclude that the normal sampling distribution can be used.
Conclusion:
B. Yes, because both \( np \) and \( nq \) are greater than or equal to 5.
Step 2: Hypotheses Formulation
The null and alternative hypotheses are stated as follows:
\[
H_0: p = 0.21
\]
\[
H_a: p \neq 0.21
\]
Step 3: Critical Value Determination
For a two-tailed test with a significance level of \( \alpha = 0.01 \), the critical z-values are calculated as:
\[
z_{\text{critical}} = \pm 2.58
\]
Step 4: Hypothesis Test Calculation
The test statistic \( Z \) is calculated using the formula:
\[
Z = \frac{\hat{p} - p_0}{\sqrt{\frac{p_0(1 - p_0)}{n}}}
\]
The p-value associated with this test statistic is:
\[
\text{P-value} = 0.0624
\]
Step 5: Conclusion of the Test
The critical region for rejection of the null hypothesis is defined as:
\[
Z < -2.5758 \quad \text{or} \quad Z > 2.5758
\]
Since the calculated test statistic \( Z \approx -1.8633 \) does not fall within the critical region, we fail to reject the null hypothesis.
Final Answer
The answer is:
\(\boxed{B}\) for the normal distribution check,
\(\boxed{H_0: p = 0.21, H_a: p \neq 0.21}\) for the hypotheses,
and the critical value(s) is/are \(\boxed{±2.58}\).