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AP Statistics 6.6 Concluding a Test for a Population Proportion- FRQs - Exam Style Questions

Question

A software application (app) lets users enter questions to receive answers in the form of images, texts, or videos. Research indicates that \(22\) percent of high school students in Country W use the app to help them with their homework at least once per week. Karen is an AP Statistics student in Country W at a high school that has more than \(2,000\) students. She believes the proportion of all students at her school who use the app to help them with their homework at least once per week is greater than the proportion for her country. To investigate her belief, she took a simple random sample of \(130\) students from her school and found that \(38\) of the sampled students use the app to help them with their homework at least once per week.
Is there convincing statistical evidence, at a \(0.05\) significance level, to support Karen’s belief? Justify your answer with the appropriate inference procedure.

Most-appropriate topic codes (CED):

TOPIC 6.4: Setting Up a Test for a Population Proportion – Main Part
TOPIC 6.5: Interpreting p-Values – Main Part
TOPIC 6.6: Concluding a Test for a Population Proportion – Main Part
▶️ Answer/Explanation
Detailed solution

State: We want to perform a hypothesis test to determine if there is convincing evidence that the proportion of all students at Karen’s school who use the app for homework at least once per week is greater than \(0.22\). Let \(p\) be this true proportion. The hypotheses are: \[ H_0: p = 0.22 \] \[ H_a: p > 0.22 \] We will use a significance level of \(\alpha = 0.05\).

Plan: The appropriate inference procedure is a one-sample z-test for a population proportion. We need to check the conditions:

  1. Random: Karen took a simple random sample of \(130\) students. Condition met.
  2. \(10\%\) Condition (Independence): The school has more than \(2,000\) students. \(130 \le 0.10(2000) = 200\). Sampling without replacement is okay. Condition met.
  3. Large Counts (Normality): Check \(np_0 \ge 10\) and \(n(1-p_0) \ge 10\).
    • \(130(0.22) = 28.6 \ge 10\)
    • \(130(1-0.22) = 130(0.78) = 101.4 \ge 10\)

    Condition met. The sampling distribution of \(\hat{p}\) is approximately normal.

Do: The sample proportion is \(\hat{p} = \frac{38}{130} \approx 0.2923\).
The standard error under \(H_0\) is: \[ \sigma_{\hat{p}} = \sqrt{\frac{p_0(1-p_0)}{n}} = \sqrt{\frac{0.22(0.78)}{130}} \approx 0.0363 \] The test statistic is: \[ z = \frac{\hat{p} – p_0}{\sigma_{\hat{p}}} = \frac{0.2923 – 0.22}{0.0363} \approx 1.99 \] The p-value is the probability of observing a test statistic \( \ge 1.99 \), assuming \(H_0\) is true: \[ \text{p-value} = P(Z \ge 1.99) \approx 0.0233 \]

Conclude: Since the p-value (\(\approx 0.0233\)) is less than the significance level (\(\alpha = 0.05\)), we reject \(H_0\). There is convincing statistical evidence that the proportion of all students at Karen’s high school who use the app to help them with their homework at least once per week is greater than the national proportion of \(0.22\).

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