Question 1

SCENARIO 8-16
A random sample of 100 stores from a large chain of 500 garden supply stores was selected to determine the mean number of lawnmowers sold at an end-of-season clearance sale.The sample results indicated a mean of 6 and a standard deviation of 2 lawnmowers sold.A 95% confidence interval (5.623 to 6.377)was established based on these results.
-Referring to Scenario 8-16,of all possible samples of 100 stores taken from the population of 1,000 stores,95% of the confidence intervals developed will contain the true population mean within the interval.

Accepted Answer

The interval 5.623 to 6.377 is a 95% confidence interval, which means that out of all possible samples of 100 stores, 95% of the confidence intervals developed will contain the true population mean within the interval. Therefore, the statement is true.

Question 2

SCENARIO 8-16
A random sample of 100 stores from a large chain of 500 garden supply stores was selected to determine the mean number of lawnmowers sold at an end-of-season clearance sale.The sample results indicated a mean of 6 and a standard deviation of 2 lawnmowers sold.A 95% confidence interval (5.623 to 6.377)was established based on these results.
-Referring to Scenario 8-16,there are 10 possible samples of 100 stores that can be selected out of the population of 1,000 stores.

Accepted Answer

The number of possible samples of 100 stores that can be selected from a population of 500 stores is significantly larger than 10. It is calculated using combinations, specifically the formula for combinations is $C(n, k) = \frac{n!}{k!(n-k)!}$, where $n$ is the total number of items (in this case, stores), and $k$ is the number of items to choose (in this case, 100 stores). This calculation would yield a much larger number than 10, indicating a vast number of possible samples.

Question 3

SCENARIO 8-16
A random sample of 100 stores from a large chain of 500 garden supply stores was selected to determine the mean number of lawnmowers sold at an end-of-season clearance sale.The sample results indicated a mean of 6 and a standard deviation of 2 lawnmowers sold.A 95% confidence interval (5.623 to 6.377)was established based on these results.
-Referring to Scenario 8-16,95% of the stores have sold between 5.623 and 6.377 lawnmowers.

Accepted Answer

The confidence interval (5.623 to 6.377) estimates the range in which the true mean number of lawnmowers sold by all stores is likely to fall, not the number of lawnmowers sold by 95% of the stores.

Question 4

SCENARIO 8-16
A random sample of 100 stores from a large chain of 500 garden supply stores was selected to determine the mean number of lawnmowers sold at an end-of-season clearance sale.The sample results indicated a mean of 6 and a standard deviation of 2 lawnmowers sold.A 95% confidence interval (5.623 to 6.377)was established based on these results.
-Referring to Scenario 8-16,we do not know for sure whether the true population mean is between 5.623 and 6.377 lawnmowers sold.

Accepted Answer

This statement is true because the confidence interval only provides an estimate of the range of values within which the true population mean is likely to fall, with a given level of confidence. It does not guarantee that the true population mean falls within this range with 100% certainty.

Question 5

SCENARIO 8-17
A wealthy real estate investor wants to decide whether it is a good investment to build a high-end shopping complex in a suburban county in Chicago.His main concern is the total market value of the 3,605 houses in the suburban county.He commissioned a statistical consulting group to take a sample of 200 houses and obtained a sample mean market price of $225,000 and a sample standard deviation of $38,700.The consulting group also found out that the mean differences between market prices and appraised prices was $125,000 with a standard deviation of $3,400.Also,the proportion of houses in the sample that are appraised for higher than the market prices is 0.24.
-Referring to Scenario 8-17,if he wants a 95% confidence on estimating the true population mean market price of the houses in the suburban county to be within $10,000,how large a sample will he need?

Accepted Answer

The answer of SCENARIO 8-17
A wealthy real estate investor wants...

Question 6

SCENARIO 8-17
A wealthy real estate investor wants to decide whether it is a good investment to build a high-end shopping complex in a suburban county in Chicago.His main concern is the total market value of the 3,605 houses in the suburban county.He commissioned a statistical consulting group to take a sample of 200 houses and obtained a sample mean market price of $225,000 and a sample standard deviation of $38,700.The consulting group also found out that the mean differences between market prices and appraised prices was $125,000 with a standard deviation of $3,400.Also,the proportion of houses in the sample that are appraised for higher than the market prices is 0.24.
-Referring to Scenario 8-17,what will be the 90% confidence interval for the mean market price of the houses in the suburban county constructed by the consulting group?

Accepted Answer

The answer of SCENARIO 8-17
A wealthy real estate investor wants...

Question 7

SCENARIO 8-17
A wealthy real estate investor wants to decide whether it is a good investment to build a high-end shopping complex in a suburban county in Chicago.His main concern is the total market value of the 3,605 houses in the suburban county.He commissioned a statistical consulting group to take a sample of 200 houses and obtained a sample mean market price of $225,000 and a sample standard deviation of $38,700.The consulting group also found out that the mean differences between market prices and appraised prices was $125,000 with a standard deviation of $3,400.Also,the proportion of houses in the sample that are appraised for higher than the market prices is 0.24.
-Referring to Scenario 8-17,what will be the 90% confidence interval for the population proportion of houses that will be appraised for higher than the market prices?

Accepted Answer

The answer of SCENARIO 8-17
A wealthy real estate investor wants...

Question 8

Bootstrapping is used to construct an interval estimate for the population mean when you cannot assume that the population is normally distributed,and the sample size is not large enough to apply the Central Limit Theorem.

Accepted Answer

Bootstrapping is a non-parametric resampling method that can be used when the population distribution is unknown or not normal and the sample size is not large enough to rely on the Central Limit Theorem. Bootstrapping involves creating a large number of random samples from the original sample, with replacement, and using these samples to estimate the sampling distribution of the mean. From this sampling distribution, we can construct an interval estimate for the population mean.

Question 9

Bootstrapping makes no assumption about the underlying population distribution.

Accepted Answer

Bootstrapping is a non-parametric method and does not make assumptions about the population distribution. Instead, it relies on resampling data from the sample to estimate sample statistics and make inferences about the population.

Question 10

To construct a bootstrap confidence interval estimate for the population mean,you will first select a random sample of size n with replacement from a population of size N as the initial sample.

Accepted Answer

The answer of To construct a bootstrap confidence interval estimate...

Question 11

To construct a bootstrap confidence interval estimate for the population mean,you will first select a random sample of size n without replacement from a population of size N as the initial sample.

Accepted Answer

This is true as the initial sample for constructing a bootstrap confidence interval estimate for the population mean is a random sample from the population of interest.

Question 12

To construct a bootstrap confidence interval estimate for the population mean,you will resample the initial sample by selecting n values with replacement from the n values in the initial sample for m different times.

Accepted Answer

This is the basic idea behind bootstrap confidence interval estimation.

Question 13

To construct a bootstrap confidence interval estimate for the population mean,you will resample the initial sample of size n by selecting n values without replacement from the n values in the initial sample for m different times.

Accepted Answer

In bootstrap sampling, you resample with replacement, not without replacement. This means each draw is independent, and the same value can be selected multiple times.

Question 14

To construct a bootstrap confidence interval estimate for the population mean,you will order the resampled means for the m samples that you have drawn from the initial sample of size n,use the value of the resampled mean that cuts off the smallest $\alpha$ / 2$\alpha$100% as the lower limit and the value of that cuts off the largest $\alpha$ / 2$\alpha$100% as the upper limit.

Accepted Answer

This is the correct method for constructing a bootstrap confidence interval estimate for the population mean.

Question 15

To construct bootstrap confidence interval estimate for the population mean with
confidence level (1-$\alpha$)100% ,you will order the resampled means for the S1S1P0S1U1P1m S1S1P0S1U1P1samples that youS1S1P0
have drawn from the initial sample of size n,use the value of the resampled mean that cuts off the largest $\alpha$ / 2$\alpha$100% as the lower limit and the value of that cuts off the smallest $\alpha$ / 2$\alpha$100% as the upper limit.

Accepted Answer

The answer of To construct bootstrap confidence interval estimate for...

Question 16

To construct bootstrap confidence interval estimate for the population mean with confidence  level(1-$\alpha$)100% ,  you  will  order   the   resampled  means  for  the  m samples that you
have drawn from the initial sample of size n,use the value of the resampled mean that cuts off the smallest $\alpha$ / 2$\alpha$100% as the lower limit and the value of that cuts off the largest $\alpha$ / 2$\alpha$100% as the upper limit.

Accepted Answer

This is the correct process for constructing a bootstrap confidence interval estimate for the population mean.

Question 17

To construct a bootstrap confidence interval estimate with confidence level
(1-$\alpha$)100%  for the population mean,you will order the resampled means for the  m  samples that you have drawn from the initial sample of size n,use the value of the resampled mean that cuts off the smallest $\alpha$100% as the lower limit and the value of that cuts off the largest $\alpha$100% as the upper limit.

Accepted Answer

The answer of To construct a bootstrap confidence interval estimate...

Question 18

The bootstrap confidence interval estimate for the population mean is constructed based on the sampling distribution of the m resampled means.

Accepted Answer

The bootstrap confidence interval estimate is constructed based on the resampled means, which makes up the estimated sampling distribution of the mean. The confidence interval is then calculated using the standard error and a Z-score or t-score.

Question 19

The bootstrap confidence interval estimate for the population mean is constructed based on the sampling distribution of the m population means.

Accepted Answer

The bootstrap confidence interval estimate for the population mean is constructed based on resampling from the original sample data, not from the sampling distribution of population means.

Question 20

To construct a bootstrap confidence interval estimate for the population mean,you typically select a very large number (in the thousands)of resamples.

Accepted Answer

This is true. Selecting a large number of resamples in the bootstrap process helps to reduce the variability of the estimate and improve the accuracy of the confidence interval.

Quiz 22: Binomial Distribution and Normal Approximation

Bootstrapping is used to construct an interval estimate for the population mean when you cannot assume that the population is normally distributed,and the sample size is not large enough to apply the Central Limit Theorem.

Bootstrapping makes no assumption about the underlying population distribution.

To construct a bootstrap confidence interval estimate for the population mean,you will first select a random sample of size n with replacement from a population of size N as the initial sample.

To construct a bootstrap confidence interval estimate for the population mean,you will first select a random sample of size n without replacement from a population of size N as the initial sample.

To construct a bootstrap confidence interval estimate for the population mean,you will resample the initial sample by selecting n values with replacement from the n values in the initial sample for m different times.

To construct a bootstrap confidence interval estimate for the population mean,you will resample the initial sample of size n by selecting n values without replacement from the n values in the initial sample for m different times.

The bootstrap confidence interval estimate for the population mean is constructed based on the sampling distribution of the m resampled means.

The bootstrap confidence interval estimate for the population mean is constructed based on the sampling distribution of the m population means.

To construct a bootstrap confidence interval estimate for the population mean,you typically select a very large number (in the thousands)of resamples.