Consider the following hypothesis test: Ho: μ < 12 Ha: μ > 12 A sample of 25 provided a sample mean = 14 and a sample standard deviation s = 4.32. a. Compute the value of the test statistic (to 2 decimals). b. Use the t distribution table (Table 2 in Appendix B) to compute a range for the p-value. The p-value is between 0.005 and 0.01 c. At a = 0.05, what is your conclusion? Reject null hypothesis d. What is the rejection rule using the critical value? (Use a = 0.05.) Reject Ho if t is less than or equal to ✓the critical value of Can you conclude that the population mean is greater than 12? No (to 3 decimals).

MATLAB: An Introduction with Applications
6th Edition
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Author:Amos Gilat
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Chapter1: Starting With Matlab
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### Hypothesis Testing Example

Consider the following hypothesis test:

- Null Hypothesis (\(H_0\)): \(\mu \leq 12\)
- Alternative Hypothesis (\(H_a\)): \(\mu > 12\)

**Sample Information:**

- Sample size (\(n\)): 25
- Sample mean (\(\bar{x}\)): 14
- Sample standard deviation (\(s\)): 4.32

**Steps:**

**a. Compute the value of the test statistic (to 2 decimals).**

[Value to be provided by the user]

**b. Use the t distribution table (Table 2 in Appendix B) to compute a range for the p-value.**

- The p-value is: **between 0.005 and 0.01** (selected from a dropdown menu)

**c. At \(\alpha = 0.05\), what is your conclusion?**

- Decision: **Reject null hypothesis** (selected from a dropdown menu)

**d. What is the rejection rule using the critical value? (Use \(\alpha = 0.05\).)**

- Reject \(H_0\) if \(t\) is **less than or equal to** the critical value of [Value to be provided by the user] (to 3 decimals).

**Conclusion:**

- Can you conclude that the population mean is greater than 12? 
  - **No** (selected from a dropdown menu)

This example demonstrates hypothesis testing, utilizing a t-test to determine if there is significant evidence to support the claim that the population mean is greater than 12. The decision-making is based on the calculated p-value and critical values in relation to the significance level \(\alpha\).
Transcribed Image Text:### Hypothesis Testing Example Consider the following hypothesis test: - Null Hypothesis (\(H_0\)): \(\mu \leq 12\) - Alternative Hypothesis (\(H_a\)): \(\mu > 12\) **Sample Information:** - Sample size (\(n\)): 25 - Sample mean (\(\bar{x}\)): 14 - Sample standard deviation (\(s\)): 4.32 **Steps:** **a. Compute the value of the test statistic (to 2 decimals).** [Value to be provided by the user] **b. Use the t distribution table (Table 2 in Appendix B) to compute a range for the p-value.** - The p-value is: **between 0.005 and 0.01** (selected from a dropdown menu) **c. At \(\alpha = 0.05\), what is your conclusion?** - Decision: **Reject null hypothesis** (selected from a dropdown menu) **d. What is the rejection rule using the critical value? (Use \(\alpha = 0.05\).)** - Reject \(H_0\) if \(t\) is **less than or equal to** the critical value of [Value to be provided by the user] (to 3 decimals). **Conclusion:** - Can you conclude that the population mean is greater than 12? - **No** (selected from a dropdown menu) This example demonstrates hypothesis testing, utilizing a t-test to determine if there is significant evidence to support the claim that the population mean is greater than 12. The decision-making is based on the calculated p-value and critical values in relation to the significance level \(\alpha\).
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