age lifetime of its lightbulbs is equal to 36 months. A random sample of 64 bulbs has a mean lifetime of 32 months, and the sample standard deviation is 11 months. We will be using a z-test for the population mean at x = 0.05 to check the manufacturer's claim. A critical value for this test is: 1.645 1.96 2.31 2.821

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**Hypothesis Testing for Lightbulb Lifetime**

A manufacturer claims that the average lifetime of its lightbulbs is equal to 36 months. To verify this claim, we'll perform a z-test for the population mean with a significance level (\(\alpha\)) of 0.05.

**Given Data:**
- The claimed average lifetime (\(\mu\)) = 36 months
- Sample size (\(n\)) = 64 bulbs
- Sample mean (\(\overline{x}\)) = 32 months
- Sample standard deviation (\(s\)) = 11 months

**Objective:**
To check the manufacturer's claim using a z-test at a significance level of 0.05.

**Question:**
A critical value for this test is:
- 1.645
- 1.96
- 2.31
- 2.821

**Explanation:**
In hypothesis testing, the critical value determines the threshold at which the null hypothesis is rejected. For a z-test, this value is based on the chosen significance level (\(\alpha\)). 

- For \(\alpha = 0.05\) in a two-tailed test, the critical value is typically 1.96.
- For a one-tailed test at \(\alpha = 0.05\), the critical value is commonly 1.645.

The correct critical value will depend on whether it’s a one-tailed or two-tailed test, assuming a normal distribution. In this scenario, determining the specific test type is crucial for selecting the accurate critical value.
Transcribed Image Text:**Hypothesis Testing for Lightbulb Lifetime** A manufacturer claims that the average lifetime of its lightbulbs is equal to 36 months. To verify this claim, we'll perform a z-test for the population mean with a significance level (\(\alpha\)) of 0.05. **Given Data:** - The claimed average lifetime (\(\mu\)) = 36 months - Sample size (\(n\)) = 64 bulbs - Sample mean (\(\overline{x}\)) = 32 months - Sample standard deviation (\(s\)) = 11 months **Objective:** To check the manufacturer's claim using a z-test at a significance level of 0.05. **Question:** A critical value for this test is: - 1.645 - 1.96 - 2.31 - 2.821 **Explanation:** In hypothesis testing, the critical value determines the threshold at which the null hypothesis is rejected. For a z-test, this value is based on the chosen significance level (\(\alpha\)). - For \(\alpha = 0.05\) in a two-tailed test, the critical value is typically 1.96. - For a one-tailed test at \(\alpha = 0.05\), the critical value is commonly 1.645. The correct critical value will depend on whether it’s a one-tailed or two-tailed test, assuming a normal distribution. In this scenario, determining the specific test type is crucial for selecting the accurate critical value.
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