A poll of 2,139 randomly selected adults showed that 92% of them own cell phones. The technology display below results from a test of the claim that 91% of adults own cell phones. Use the normal distribution as an approximation to the binomial distribution, and assume a 0.05 significance level.   identify the tests statistical, P- value, null hypotheses, two -tailed left tailed or both and the conclusion.

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A poll of 2,139 randomly selected adults showed that 92% of them own cell phones. The technology display below results from a test of the claim that 91% of adults own cell phones. Use the normal distribution as an approximation to the binomial distribution, and assume a 0.05 significance level.

 

identify the tests statistical, P- value, null hypotheses, two -tailed left tailed or both and the conclusion. 

---

**Hypothesis Testing Example**

**Test of \( p = 0.91 \) vs \( p \neq 0.91 \)**

| Sample | X   | N      | Sample p   | 95% CI                        | Z-Value | P-Value |
|--------|-----|--------|------------|-------------------------------|---------|---------|
| 1      | 1967| 2,139  | 0.919589   | (0.908065, 0.931112)          | 1.55    | 0.121   |

**a. Is the test two-tailed, left-tailed, or right-tailed?**

- ☐ Left-tailed test
- ☐ Right-tailed test
- ☐ Two-tailed test

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**Explanation of Table:**

- **Sample**: The identifier for the sample tested.
- **X**: The number of successes in the sample.
- **N**: The total number of trials in the sample.
- **Sample p**: The proportion of successes in the sample.
- **95% CI**: The 95% confidence interval for the proportion.
- **Z-Value**: The test statistic used to test the hypothesis.
- **P-Value**: The probability value associated with the Z-Value.

---

When conducting a hypothesis test, it is important to determine the direction of the test:

1. **Left-tailed test**: Tests whether the population proportion is less than the hypothesized proportion.
2. **Right-tailed test**: Tests whether the population proportion is greater than the hypothesized proportion.
3. **Two-tailed test**: Tests whether the population proportion is different from the hypothesized proportion (could be either less than or greater than).

In this example, the test is conducted for \( p = 0.91 \) vs \( p \neq 0.91 \), indicating a two-tailed test. Therefore, the option "Two-tailed test" should be selected.

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Transcribed Image Text:--- **Hypothesis Testing Example** **Test of \( p = 0.91 \) vs \( p \neq 0.91 \)** | Sample | X | N | Sample p | 95% CI | Z-Value | P-Value | |--------|-----|--------|------------|-------------------------------|---------|---------| | 1 | 1967| 2,139 | 0.919589 | (0.908065, 0.931112) | 1.55 | 0.121 | **a. Is the test two-tailed, left-tailed, or right-tailed?** - ☐ Left-tailed test - ☐ Right-tailed test - ☐ Two-tailed test --- **Explanation of Table:** - **Sample**: The identifier for the sample tested. - **X**: The number of successes in the sample. - **N**: The total number of trials in the sample. - **Sample p**: The proportion of successes in the sample. - **95% CI**: The 95% confidence interval for the proportion. - **Z-Value**: The test statistic used to test the hypothesis. - **P-Value**: The probability value associated with the Z-Value. --- When conducting a hypothesis test, it is important to determine the direction of the test: 1. **Left-tailed test**: Tests whether the population proportion is less than the hypothesized proportion. 2. **Right-tailed test**: Tests whether the population proportion is greater than the hypothesized proportion. 3. **Two-tailed test**: Tests whether the population proportion is different from the hypothesized proportion (could be either less than or greater than). In this example, the test is conducted for \( p = 0.91 \) vs \( p \neq 0.91 \), indicating a two-tailed test. Therefore, the option "Two-tailed test" should be selected. ---
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