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Suppose that in a random selection of 100 colored candies, \( 24 \% \) of them are blue. The candy company claims that the percentage of blue candies is equal to \( 30 \% \). Use a 0.10 significance level to test that claim. Identify the null and altemative hypotheses for this test. Choose the correct answer below. A. \( \mathrm{H}_{0}: \mathrm{p}=0.3 \) \[ H_{1}: p>03 \] B. \( H_{0}: p=0.3 \) \( H_{1}: p \neq 0.3 \) C. \( \mathrm{H}_{0} \cdot \mathrm{p} \neq 0.3 \) \( H_{1}: p=0.3 \) D. \( H_{0} ; p=0.3 \) \( H_{1} \) : \( p<0.3 \) Identify the test statistic for this hypothesis test. The test statistic for this hypothesis test is -1.31 . (Round to two decimal places as needed.) Identify the P-value for this hypothesis test. The P -value for this hypothesis test is \( \square \) (Round to three decimal places as needed )

Ask by Pope Bernard. in the United States
Mar 21,2025

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Answer

**Hypotheses:** - Null Hypothesis (\( H_{0} \)): The proportion of blue candies is 30% (\( p = 0.3 \)) - Alternative Hypothesis (\( H_{1} \)): The proportion of blue candies is not 30% (\( p \neq 0.3 \)) **Test Statistic:** - \(-1.31\) **P-value:** - \(0.190\)

Solution

**Step 1. State the Hypotheses** The candy company claims that the percentage of blue candies is \(30\%\). Thus, the null hypothesis is that the true proportion \(p\) of blue candies is \(0.30\). Since we want to test the claim (i.e., whether it is exactly \(30\%\) or not), the alternative hypothesis is that the true proportion is not equal to \(0.30\). This corresponds to a two-tailed test. In mathematical terms, we have: \[ H_{0}: p=0.3 \quad \text{and} \quad H_{1}: p \neq 0.3 \] This matches option B. --- **Step 2. Identify the Test Statistic** The test statistic for a proportion is given by: \[ z = \frac{\hat{p} - p_0}{\sqrt{\frac{p_0 (1-p_0)}{n}}} \] where: - \(\hat{p}\) is the sample proportion, - \(p_0\) is the claimed proportion (0.3), - \(n\) is the sample size. Given: - \(\hat{p} = 0.24\) (since \(24\%\) of 100 candies are blue), - \(p_0 = 0.3\), - \(n = 100\). Plug the values into the formula: \[ z = \frac{0.24 - 0.3}{\sqrt{\frac{0.3(1-0.3)}{100}}} = \frac{-0.06}{\sqrt{\frac{0.3 \times 0.7}{100}}} = \frac{-0.06}{\sqrt{0.21/100}} = \frac{-0.06}{\sqrt{0.0021}} = \frac{-0.06}{0.0458} \approx -1.31 \] Thus, the test statistic is \(-1.31\). --- **Step 3. Find the P-value** Since this is a two-tailed test, the p-value is calculated as: \[ \text{P-value} = 2 \times P(Z < -1.31) \] Using a standard normal table or calculator, we find: \[ P(Z < -1.31) \approx 0.095 \] Thus, \[ \text{P-value} \approx 2 \times 0.095 = 0.190 \] --- **Final Answers** 1. **Hypotheses:** \[ H_{0}: p=0.3 \quad \text{and} \quad H_{1}: p\neq 0.3 \quad \text{(Option B)} \] 2. **Test Statistic:** \[ -1.31 \] 3. **P-value:** \[ 0.190 \]

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To conduct this hypothesis test, we first need to formulate our null and alternative hypotheses. The candy company claims that 30% of the candies are blue, while our sample shows that only 24% are blue. The correct choice is: B. \( H_{0}: p=0.3 \) \( H_{1}: p \neq 0.3 \) This means we are testing if the proportion of blue candies is significantly different from 30%. Now, let's talk about the test statistic. You provided that it is -1.31. That statistic indicates how far the sample proportion is from the hypothesized population proportion under the null hypothesis, measured in standard deviations. To find the P-value associated with a test statistic of -1.31, you would typically refer to a standard normal distribution table (or use statistical software) to find the probability corresponding to that z-value. Given the two-tailed nature of your test, the P-value would be \( 2 \times P(Z < -1.31) \). As estimated, let's say the P-value is approximately \( 0.190 \) (make sure to check using a z-table for accuracy). Overall, you're testing if the proportion of blue candies significantly deviates from 30%, and your findings (statistic and P-value) will inform if you can reject the null hypothesis. Happy analyzing!

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