Thanks to an initiative to recruit top students, an administrator at a college claims that this year's entering class must have a greater mean IQ score than that entering classes from previous years. The administrator tests a random sample of 21 of this year's entering students and finds that their mean IQ score is 118 with a standard deviation of 13. The college records indicate that the mean IQ score for entering students from previous years is 113. Is there enough evidence to conclude, at the 0.10 level of significance, that the population mean IQ score, μ, of this year's class is greater than that of previo years? To answer, assume that the IQ scores of this year's entering class are approximately normally distributed. Perform a one-tailed test. Then complete the parts below. Carry your intermediate computations to three or more decimal places. (If necessary, consult a list of formulas.) (a) State the null hypothesis Ho and the alternative hypothesis H₁. H₂ :O H₁:0 (b) Determine the type of test statistic to use. (Choose one) ▼ (c) Find the value of the test statistic. (Round to three or more decimal places.) H |x X a □□ S P 8 00 Р 0=0 OSO 020

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**Educational Content on Hypothesis Testing**

In an effort to attract top students, a college administrator claims that the current entering class has a higher mean IQ score compared to previous years. A sample of 21 students from this year's class shows a mean IQ score of 118, with a standard deviation of 13. Historically, the mean IQ score for entering students was 113.

The question posed is whether there is enough evidence to conclude, at a 0.10 level of significance, that this year's class has a higher mean IQ score than previous classes. Assume the IQ scores are normally distributed for this test.

### Steps to Conduct the One-Tailed Hypothesis Test

**(a) State the Hypotheses:**

- **Null Hypothesis (H₀):** The population mean IQ score, μ, of this year's class is less than or equal to the previous years, i.e., μ ≤ 113.
  
- **Alternative Hypothesis (H₁):** The population mean IQ score, μ, of this year's class is greater than that of previous years, i.e., μ > 113.

**(b) Determine the Type of Test Statistic:**

Choose the appropriate statistical test based on sample size and known parameters. In this case, use a t-test for a single sample since the population standard deviation is unknown.

**(c) Calculate the Test Statistic:**

Use the formula for the t-statistic:

\[ t = \frac{\bar{x} - \mu}{s/\sqrt{n}} \]

Where:
- \(\bar{x} = 118\) (sample mean)
- \(\mu = 113\) (population mean under H₀)
- \(s = 13\) (sample standard deviation)
- \(n = 21\) (sample size)

**(d) Find the Critical Value:**

Determine the critical t-value from the t-distribution table based on the 0.10 level of significance (right-tailed) and the degrees of freedom (\(n-1 = 20\)).

**(e) Conclusion:**

Based on the calculated t-statistic and the critical value, decide whether to reject the null hypothesis. If the t-statistic is greater than the critical value, conclude that the mean IQ score of this year's class is significantly greater than that of previous years.

Understanding these steps aids in making informed decisions based on statistical analysis in educational settings.
Transcribed Image Text:**Educational Content on Hypothesis Testing** In an effort to attract top students, a college administrator claims that the current entering class has a higher mean IQ score compared to previous years. A sample of 21 students from this year's class shows a mean IQ score of 118, with a standard deviation of 13. Historically, the mean IQ score for entering students was 113. The question posed is whether there is enough evidence to conclude, at a 0.10 level of significance, that this year's class has a higher mean IQ score than previous classes. Assume the IQ scores are normally distributed for this test. ### Steps to Conduct the One-Tailed Hypothesis Test **(a) State the Hypotheses:** - **Null Hypothesis (H₀):** The population mean IQ score, μ, of this year's class is less than or equal to the previous years, i.e., μ ≤ 113. - **Alternative Hypothesis (H₁):** The population mean IQ score, μ, of this year's class is greater than that of previous years, i.e., μ > 113. **(b) Determine the Type of Test Statistic:** Choose the appropriate statistical test based on sample size and known parameters. In this case, use a t-test for a single sample since the population standard deviation is unknown. **(c) Calculate the Test Statistic:** Use the formula for the t-statistic: \[ t = \frac{\bar{x} - \mu}{s/\sqrt{n}} \] Where: - \(\bar{x} = 118\) (sample mean) - \(\mu = 113\) (population mean under H₀) - \(s = 13\) (sample standard deviation) - \(n = 21\) (sample size) **(d) Find the Critical Value:** Determine the critical t-value from the t-distribution table based on the 0.10 level of significance (right-tailed) and the degrees of freedom (\(n-1 = 20\)). **(e) Conclusion:** Based on the calculated t-statistic and the critical value, decide whether to reject the null hypothesis. If the t-statistic is greater than the critical value, conclude that the mean IQ score of this year's class is significantly greater than that of previous years. Understanding these steps aids in making informed decisions based on statistical analysis in educational settings.
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