c) If you take a sample of size 36, can you say what the shape of the distribution of the sample mean is? v ? Yes No vhy not? population is normal population is not normal o is known On is at least 30 On is less than 30 Oo is unknown d) For a sample of size 36, state the mean and the standard deviation of the sampling distribution of the sample mean. mean of the sampling distribution of the sample meanwhen n = 36: standard deviation of the sampling distribution of the sample mean when n = 36 rounded to two decimal places: O O O O O
c) If you take a sample of size 36, can you say what the shape of the distribution of the sample mean is? v ? Yes No vhy not? population is normal population is not normal o is known On is at least 30 On is less than 30 Oo is unknown d) For a sample of size 36, state the mean and the standard deviation of the sampling distribution of the sample mean. mean of the sampling distribution of the sample meanwhen n = 36: standard deviation of the sampling distribution of the sample mean when n = 36 rounded to two decimal places: O O O O O
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Topic Video
Question
![### Sampling Distribution and Sample Mean
#### Question c
**Prompt:** If you take a sample of size 36, can you say what the shape of the distribution of the sample mean is?
**Options:**
- Yes [Selected]
- No
**Explain why or why not:**
- [ ] population is normal
- [ ] population is not normal
- [ ] σ (sigma) is known
- [ ] n is at least 30
- [ ] n is less than 30
- [ ] σ (sigma) is unknown
#### Question d
For a sample of size 36, state the mean and the standard deviation of the sampling distribution of the sample mean.
- **Mean of the sampling distribution of the sample mean when n = 36:**
(Input box)
- **Standard deviation of the sampling distribution of the sample mean when n = 36 rounded to two decimal places:**
(Input box)
These exercises explore the characteristics of the sampling distribution of the sample mean, using the Central Limit Theorem and its assumptions depending on the sample size \( n \).](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F170e3780-ffa2-4c07-bf27-8e02aea9a195%2F5adbdeca-e589-4024-865f-c8df959bfc82%2Fkdvjxnk_processed.png&w=3840&q=75)
Transcribed Image Text:### Sampling Distribution and Sample Mean
#### Question c
**Prompt:** If you take a sample of size 36, can you say what the shape of the distribution of the sample mean is?
**Options:**
- Yes [Selected]
- No
**Explain why or why not:**
- [ ] population is normal
- [ ] population is not normal
- [ ] σ (sigma) is known
- [ ] n is at least 30
- [ ] n is less than 30
- [ ] σ (sigma) is unknown
#### Question d
For a sample of size 36, state the mean and the standard deviation of the sampling distribution of the sample mean.
- **Mean of the sampling distribution of the sample mean when n = 36:**
(Input box)
- **Standard deviation of the sampling distribution of the sample mean when n = 36 rounded to two decimal places:**
(Input box)
These exercises explore the characteristics of the sampling distribution of the sample mean, using the Central Limit Theorem and its assumptions depending on the sample size \( n \).
![**A random variable X is not normally distributed. It has a mean of 33 and a standard deviation of 7.**
**List the givens with correct symbols:**
- \(\mu = 33\)
- \(\sigma = 7\)
**a) If you take a sample of size 17, can you say what the shape of the sampling distribution for the sample mean is?**
- (Dropdown menu: \(\sigma\), \(X\), \(p\), \(N\), \(s\), \(\overline{X}\), \(\mu\), \(n\))
**Why or why not? Check all that apply.**
- [ ] \(\sigma\) is unknown
- [x] \(n\) is less than 30
- [ ] \(\sigma\) is known
- [ ] \(n\) is at least 30
- [x] population is not normal
- [ ] population is normal
**b) For a sample of size 17, state the mean and the standard deviation of the sampling distribution of the sample mean.**
- **Mean of the sampling distribution of the sample mean when \(n = 17\):** \(\_\_\_\_\_\_\_\_\_)
- **Standard deviation of the sampling distribution of the sample mean when \(n = 17\) rounded to two decimal places:** \(\_\_\_\_\_\_\_\_\_\_\)
**c) If you take a sample of size 36, can you say what the shape of the distribution of the sample mean is?**
---
**Notes:**
- The dropdown and checkboxes are likely part of an interactive exercise for students to complete.
- The exercise involves understanding sampling distributions and the Central Limit Theorem, particularly how sample size affects the distribution of the sample mean.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F170e3780-ffa2-4c07-bf27-8e02aea9a195%2F5adbdeca-e589-4024-865f-c8df959bfc82%2Fyq3w4ar_processed.png&w=3840&q=75)
Transcribed Image Text:**A random variable X is not normally distributed. It has a mean of 33 and a standard deviation of 7.**
**List the givens with correct symbols:**
- \(\mu = 33\)
- \(\sigma = 7\)
**a) If you take a sample of size 17, can you say what the shape of the sampling distribution for the sample mean is?**
- (Dropdown menu: \(\sigma\), \(X\), \(p\), \(N\), \(s\), \(\overline{X}\), \(\mu\), \(n\))
**Why or why not? Check all that apply.**
- [ ] \(\sigma\) is unknown
- [x] \(n\) is less than 30
- [ ] \(\sigma\) is known
- [ ] \(n\) is at least 30
- [x] population is not normal
- [ ] population is normal
**b) For a sample of size 17, state the mean and the standard deviation of the sampling distribution of the sample mean.**
- **Mean of the sampling distribution of the sample mean when \(n = 17\):** \(\_\_\_\_\_\_\_\_\_)
- **Standard deviation of the sampling distribution of the sample mean when \(n = 17\) rounded to two decimal places:** \(\_\_\_\_\_\_\_\_\_\_\)
**c) If you take a sample of size 36, can you say what the shape of the distribution of the sample mean is?**
---
**Notes:**
- The dropdown and checkboxes are likely part of an interactive exercise for students to complete.
- The exercise involves understanding sampling distributions and the Central Limit Theorem, particularly how sample size affects the distribution of the sample mean.
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