To explain how these histograms demonstrate what the central limit theorem says about the sampling distribution.

Question

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Answer 1

Question

Chapter 18, Problem 1E

To determine

To explain how these histograms demonstrate what the central limit theorem says about the sampling distribution.

Expert Solution & Answer

Explanation of Solution

In the question, four histograms are given of the response rates of the mails that are send. Thus, the four histograms are of different sample sizes as of size 20,50,100,200 respectively. So, these histograms demonstrate the central limit theorem says about the sampling distribution that by looking at the graphs the histograms are all centred around 0.05 . As n (the sample size) increases the results get more accurate and the histogram get into a more normal shape. Also by increasing n , the results will not be as scattered. Thus, by looking at the histogram of the sample size 20 , we see that it is approximately right skewed as the bars are starting from the larger and then moving towards smaller bars. Now, for the histogram of the sample size 50,100,200 , we can say that it they are all in the shape of the bell, so they are approximately symmetric in nature. And they all are approximately normally distributed histograms.

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Answer 2

Question

Chapter 18, Problem 1E

To determine

To explain how these histograms demonstrate what the central limit theorem says about the sampling distribution.

Expert Solution & Answer

Explanation of Solution

In the question, four histograms are given of the response rates of the mails that are send. Thus, the four histograms are of different sample sizes as of size 20,50,100,200 respectively. So, these histograms demonstrate the central limit theorem says about the sampling distribution that by looking at the graphs the histograms are all centred around 0.05 . As n (the sample size) increases the results get more accurate and the histogram get into a more normal shape. Also by increasing n , the results will not be as scattered. Thus, by looking at the histogram of the sample size 20 , we see that it is approximately right skewed as the bars are starting from the larger and then moving towards smaller bars. Now, for the histogram of the sample size 50,100,200 , we can say that it they are all in the shape of the bell, so they are approximately symmetric in nature. And they all are approximately normally distributed histograms.

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Answer 3

Question

Chapter 18, Problem 1E

To determine

To explain how these histograms demonstrate what the central limit theorem says about the sampling distribution.

Expert Solution & Answer

Explanation of Solution

In the question, four histograms are given of the response rates of the mails that are send. Thus, the four histograms are of different sample sizes as of size 20,50,100,200 respectively. So, these histograms demonstrate the central limit theorem says about the sampling distribution that by looking at the graphs the histograms are all centred around 0.05 . As n (the sample size) increases the results get more accurate and the histogram get into a more normal shape. Also by increasing n , the results will not be as scattered. Thus, by looking at the histogram of the sample size 20 , we see that it is approximately right skewed as the bars are starting from the larger and then moving towards smaller bars. Now, for the histogram of the sample size 50,100,200 , we can say that it they are all in the shape of the bell, so they are approximately symmetric in nature. And they all are approximately normally distributed histograms.

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Answer 4

Question

Chapter 18, Problem 1E

To determine

To explain how these histograms demonstrate what the central limit theorem says about the sampling distribution.

Expert Solution & Answer

Explanation of Solution

In the question, four histograms are given of the response rates of the mails that are send. Thus, the four histograms are of different sample sizes as of size 20,50,100,200 respectively. So, these histograms demonstrate the central limit theorem says about the sampling distribution that by looking at the graphs the histograms are all centred around 0.05 . As n (the sample size) increases the results get more accurate and the histogram get into a more normal shape. Also by increasing n , the results will not be as scattered. Thus, by looking at the histogram of the sample size 20 , we see that it is approximately right skewed as the bars are starting from the larger and then moving towards smaller bars. Now, for the histogram of the sample size 50,100,200 , we can say that it they are all in the shape of the bell, so they are approximately symmetric in nature. And they all are approximately normally distributed histograms.

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Answer 5

Chapter 18, Problem 1E

To determine

To explain how these histograms demonstrate what the central limit theorem says about the sampling distribution.

Expert Solution & Answer

Explanation of Solution

In the question, four histograms are given of the response rates of the mails that are send. Thus, the four histograms are of different sample sizes as of size 20,50,100,200 respectively. So, these histograms demonstrate the central limit theorem says about the sampling distribution that by looking at the graphs the histograms are all centred around 0.05 . As n (the sample size) increases the results get more accurate and the histogram get into a more normal shape. Also by increasing n , the results will not be as scattered. Thus, by looking at the histogram of the sample size 20 , we see that it is approximately right skewed as the bars are starting from the larger and then moving towards smaller bars. Now, for the histogram of the sample size 50,100,200 , we can say that it they are all in the shape of the bell, so they are approximately symmetric in nature. And they all are approximately normally distributed histograms.

Answer 6

Chapter 18, Problem 1E

To determine

To explain how these histograms demonstrate what the central limit theorem says about the sampling distribution.

Expert Solution & Answer

Explanation of Solution

In the question, four histograms are given of the response rates of the mails that are send. Thus, the four histograms are of different sample sizes as of size 20,50,100,200 respectively. So, these histograms demonstrate the central limit theorem says about the sampling distribution that by looking at the graphs the histograms are all centred around 0.05 . As n (the sample size) increases the results get more accurate and the histogram get into a more normal shape. Also by increasing n , the results will not be as scattered. Thus, by looking at the histogram of the sample size 20 , we see that it is approximately right skewed as the bars are starting from the larger and then moving towards smaller bars. Now, for the histogram of the sample size 50,100,200 , we can say that it they are all in the shape of the bell, so they are approximately symmetric in nature. And they all are approximately normally distributed histograms.

Answer 7

Chapter 18, Problem 1E

To determine

To explain how these histograms demonstrate what the central limit theorem says about the sampling distribution.

Answer 8

Expert Solution & Answer

Explanation of Solution

In the question, four histograms are given of the response rates of the mails that are send. Thus, the four histograms are of different sample sizes as of size 20,50,100,200 respectively. So, these histograms demonstrate the central limit theorem says about the sampling distribution that by looking at the graphs the histograms are all centred around 0.05 . As n (the sample size) increases the results get more accurate and the histogram get into a more normal shape. Also by increasing n , the results will not be as scattered. Thus, by looking at the histogram of the sample size 20 , we see that it is approximately right skewed as the bars are starting from the larger and then moving towards smaller bars. Now, for the histogram of the sample size 50,100,200 , we can say that it they are all in the shape of the bell, so they are approximately symmetric in nature. And they all are approximately normally distributed histograms.