What hypothesis testing procedure should you use to answer these questions? Assume all samples are simple random samples, and assume x = 0.05 if it isn't specified. A company wishes to purchase a new machine to produce ball bearings since the new machine is faster, and so will produce more ball bearings than the old machine. They decide to purchase the new machine only if the mean strength of the bearings is not less than the old machine. The old machine produces bearings that can withstand 400 lbs per square inch. The company is allowed to test the new machine for a day, so they produce 100 ball bearings under the usual operating conditions on the new machine. They find that the average strength to be approximately 398.5 lbs per square inch and the SD to be about 5 lbs per square inch. The sample distribution does not look normal. Should the company purchase the new machine, at x = 0.05? One sample z-test for the population mean. Two sample z-test for the population means. One sample z-test for proportions. Two sample z-test for proportions. One sample t-test for the population mean. None of our hypothesis tests fit. 22

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### Hypothesis Testing: Choosing the Appropriate Procedure

When performing hypothesis testing to address specific research questions, selecting the correct testing procedure is crucial. Assume all samples are simple random samples, and use a significance level (α) of 0.05 if not specified.

#### Scenario:
A company is considering purchasing a new machine that is purportedly more efficient for producing ball bearings. Their decision hinges on whether the mean strength of bearings from the new machine is at least as strong as those from the old machine. The old machine produces ball bearings capable of withstanding 400 lbs per square inch.

To test the new machine's performance:
- The company tests 100 ball bearings from the new machine under standard operating conditions.
- The average strength is found to be approximately 398.5 lbs per square inch.
- The standard deviation (SD) is about 5 lbs per square inch.
- The sample distribution appears non-normal.

#### Question:
Based on the above scenario, should the company purchase the new machine at α = 0.05?

Which hypothesis testing procedure should be used?
- One sample z-test for the population mean.
- Two sample z-test for the population means.
- One sample z-test for proportions.
- Two sample z-test for proportions.
- One sample t-test for the population mean.
- None of our hypothesis tests fit.

#### Explanation:

The correct hypothesis test to use in this scenario is pertinent to several factors:
1. We are comparing the mean strength of ball bearings from the new machine against the known mean strength of 400 lbs per square inch from the old machine.
2. The sample size is 100 ball bearings.
3. The distribution of sample data does not appear normal.
4. The standard deviation is given.

Given that the sample distribution does not follow a normal distribution and the sample size is relatively large, the appropriate test would generally be a **one-sample t-test for the population mean**; however, using a z-test could be considered if the sample size is sufficiently large for the Central Limit Theorem to apply, assuming normality of the sampling distribution.

**Selected Procedure:**
- **One sample t-test for the population mean.**

To see the details of hypothesis testing procedures, you can refer to our statistics resource section.

---

In this educational context, the explanation provides a clear understanding of why a specific hypothesis test is selected, considering the data characteristics and scenario requirements.
Transcribed Image Text:### Hypothesis Testing: Choosing the Appropriate Procedure When performing hypothesis testing to address specific research questions, selecting the correct testing procedure is crucial. Assume all samples are simple random samples, and use a significance level (α) of 0.05 if not specified. #### Scenario: A company is considering purchasing a new machine that is purportedly more efficient for producing ball bearings. Their decision hinges on whether the mean strength of bearings from the new machine is at least as strong as those from the old machine. The old machine produces ball bearings capable of withstanding 400 lbs per square inch. To test the new machine's performance: - The company tests 100 ball bearings from the new machine under standard operating conditions. - The average strength is found to be approximately 398.5 lbs per square inch. - The standard deviation (SD) is about 5 lbs per square inch. - The sample distribution appears non-normal. #### Question: Based on the above scenario, should the company purchase the new machine at α = 0.05? Which hypothesis testing procedure should be used? - One sample z-test for the population mean. - Two sample z-test for the population means. - One sample z-test for proportions. - Two sample z-test for proportions. - One sample t-test for the population mean. - None of our hypothesis tests fit. #### Explanation: The correct hypothesis test to use in this scenario is pertinent to several factors: 1. We are comparing the mean strength of ball bearings from the new machine against the known mean strength of 400 lbs per square inch from the old machine. 2. The sample size is 100 ball bearings. 3. The distribution of sample data does not appear normal. 4. The standard deviation is given. Given that the sample distribution does not follow a normal distribution and the sample size is relatively large, the appropriate test would generally be a **one-sample t-test for the population mean**; however, using a z-test could be considered if the sample size is sufficiently large for the Central Limit Theorem to apply, assuming normality of the sampling distribution. **Selected Procedure:** - **One sample t-test for the population mean.** To see the details of hypothesis testing procedures, you can refer to our statistics resource section. --- In this educational context, the explanation provides a clear understanding of why a specific hypothesis test is selected, considering the data characteristics and scenario requirements.
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