The following figure shows the distribution of a population with mean 0.6 00 02 04 06 08 Assume that 100 items are randomly sampled from this population and the mean of these 100 items is recorded. We then repeat this process a large number of times. Select the correct figure that represents the distribution of these sample means. 00 02 04 06 08 1.0 Sample Mean 00 02 04 06 08 10 Sample Mean 00 02 06 08 10
The following figure shows the distribution of a population with mean 0.6 00 02 04 06 08 Assume that 100 items are randomly sampled from this population and the mean of these 100 items is recorded. We then repeat this process a large number of times. Select the correct figure that represents the distribution of these sample means. 00 02 04 06 08 1.0 Sample Mean 00 02 04 06 08 10 Sample Mean 00 02 06 08 10
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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This graph is a histogram representing the population distribution, where the x-axis represents the values ranging from 0.0 to 1.0 and the y-axis represents the frequency of these values in the population. The distribution is approximately symmetric and centered around the mean value of 0.6.
#### Sampling from the Population
Assume that 100 items are randomly sampled from this population, and the mean of these 100 items is recorded. We then repeat this process a large number of times.
#### Selecting the Correct Distribution of Sample Means
Below are three figures depicting potential distributions of these sample means. Select the correct figure that represents the distribution of these sample means.
1. 
- This histogram has a mean at approximately 0.6, with a symmetric and narrow shape indicating low variance.
2. 
- This histogram shows a mean around 0.6 but with higher variability compared to the first, indicating slightly more spread.
3. 
- This histogram displays a flatter distribution with more spread around the mean of 0.6, suggesting a higher variance.
Ensure your choice reflects your understanding of how sample means behave according to the Central Limit Theorem, which states that the distribution of the sample means will tend to be normal (Gaussian), with the same mean as the population, but with reduced variability (standard error).
By selecting the correct distribution, you can apply your knowledge of statistics and probability to real-world scenarios involving sampling and estimation.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F7bf6b58d-ef43-404d-8e44-e8a8dab82f8c%2F5f105595-3d8b-4758-9ed5-00c695b11d8c%2F4ucq2sw.jpeg&w=3840&q=75)
Transcribed Image Text:### Understanding Population Distribution and Sample Means
The following figure shows the distribution of a population with a mean of 0.6.

This graph is a histogram representing the population distribution, where the x-axis represents the values ranging from 0.0 to 1.0 and the y-axis represents the frequency of these values in the population. The distribution is approximately symmetric and centered around the mean value of 0.6.
#### Sampling from the Population
Assume that 100 items are randomly sampled from this population, and the mean of these 100 items is recorded. We then repeat this process a large number of times.
#### Selecting the Correct Distribution of Sample Means
Below are three figures depicting potential distributions of these sample means. Select the correct figure that represents the distribution of these sample means.
1. 
- This histogram has a mean at approximately 0.6, with a symmetric and narrow shape indicating low variance.
2. 
- This histogram shows a mean around 0.6 but with higher variability compared to the first, indicating slightly more spread.
3. 
- This histogram displays a flatter distribution with more spread around the mean of 0.6, suggesting a higher variance.
Ensure your choice reflects your understanding of how sample means behave according to the Central Limit Theorem, which states that the distribution of the sample means will tend to be normal (Gaussian), with the same mean as the population, but with reduced variability (standard error).
By selecting the correct distribution, you can apply your knowledge of statistics and probability to real-world scenarios involving sampling and estimation.
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