Choose the correct answer below. OA. A conclusion based on a confidence interval estimate will be the same as a conclusion based on a hypothesis test. OB. If the sample results (or more extreme results) cannot easily occur when the null hypothesis is true, we explain the discrepancy between the assumption and the sample results by concluding that the assumption is true, so we do not reject the assumption. OC. If the sample results (or more extreme results) can easily occur when the null hypothesis is true, we attribute the relatively small discrepancy between the assumption and the sample to chance. OD. If, under a given assumption, there is an exceptionally small probability of getting sample results at least as extreme as the results that were obtained, we conclude that the assumptio probably not correct.

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
icon
Related questions
Question
### Testing a Claim about a Mean with Known Standard Deviation (σ)

#### Question:
Which of the following is NOT a requirement for testing a claim about a mean with σ known?

#### Answer choices:
**Choose the correct answer below:**

- **A.** A conclusion based on a confidence interval estimate will be the same as a conclusion based on a hypothesis test.
- **B.** If the sample results (or more extreme results) cannot easily occur when the null hypothesis is true, we explain the discrepancy between the assumption and the sample results by concluding that the assumption is true, so we do not reject the assumption.
- **C.** If the sample results (or more extreme results) can easily occur when the null hypothesis is true, we attribute the relatively small discrepancy between the assumption and the sample results to chance.
- **D.** If, under a given assumption, there is an exceptionally small probability of getting sample results at least as extreme as the results that were obtained, we conclude that the assumption is probably not correct.

---

In this context, a mean with a known standard deviation (σ) refers to situations where the standard deviation of the population is a known quantity. Here, hypothesis testing involves making a claim about the population mean and then using sample data to make inferences. 

Understanding which answer is NOT a requirement is key for discerning the fundamentals of conducting hypothesis tests effectively.

##### Explanation of Answer Choices:
- **A:** This statement suggests equivalence between conclusions drawn from confidence intervals and hypothesis tests. Although related, the methods are not always equivalent in their conclusions, making this a potentially misleading requirement.
- **B:** This describes a situation consistent with failing to reject the null hypothesis when sample results do not contradict it.
- **C:** This refers to attributing minor discrepancies to random variability when results align with the null hypothesis being true, which aligns with the foundation of hypothesis testing.
- **D:** This describes rejecting the null hypothesis when extreme sample results suggest the underlying assumption is likely incorrect, following the logic of hypothesis testing.

The correct answer should identify the statement that does not align strictly with the requirements of hypothesis testing procedures.
Transcribed Image Text:### Testing a Claim about a Mean with Known Standard Deviation (σ) #### Question: Which of the following is NOT a requirement for testing a claim about a mean with σ known? #### Answer choices: **Choose the correct answer below:** - **A.** A conclusion based on a confidence interval estimate will be the same as a conclusion based on a hypothesis test. - **B.** If the sample results (or more extreme results) cannot easily occur when the null hypothesis is true, we explain the discrepancy between the assumption and the sample results by concluding that the assumption is true, so we do not reject the assumption. - **C.** If the sample results (or more extreme results) can easily occur when the null hypothesis is true, we attribute the relatively small discrepancy between the assumption and the sample results to chance. - **D.** If, under a given assumption, there is an exceptionally small probability of getting sample results at least as extreme as the results that were obtained, we conclude that the assumption is probably not correct. --- In this context, a mean with a known standard deviation (σ) refers to situations where the standard deviation of the population is a known quantity. Here, hypothesis testing involves making a claim about the population mean and then using sample data to make inferences. Understanding which answer is NOT a requirement is key for discerning the fundamentals of conducting hypothesis tests effectively. ##### Explanation of Answer Choices: - **A:** This statement suggests equivalence between conclusions drawn from confidence intervals and hypothesis tests. Although related, the methods are not always equivalent in their conclusions, making this a potentially misleading requirement. - **B:** This describes a situation consistent with failing to reject the null hypothesis when sample results do not contradict it. - **C:** This refers to attributing minor discrepancies to random variability when results align with the null hypothesis being true, which aligns with the foundation of hypothesis testing. - **D:** This describes rejecting the null hypothesis when extreme sample results suggest the underlying assumption is likely incorrect, following the logic of hypothesis testing. The correct answer should identify the statement that does not align strictly with the requirements of hypothesis testing procedures.
Expert Solution
steps

Step by step

Solved in 4 steps

Blurred answer
Similar questions
Recommended textbooks for you
MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
Elementary Statistics: Picturing the World (7th E…
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
The Basic Practice of Statistics
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
Introduction to the Practice of Statistics
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman