To identify:An important assumption for using the bootstrap method

sjeikdom0
2020-11-08
Answered

To identify:An important assumption for using the bootstrap method

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Nichole Watt

Answered 2020-11-09
Author has **100** answers

Reason for the correct answer:

The sampling distribution of the sample median does not follow a normal distribution.

Thus, the correct option is (b).

Reasons for the incorrect answers:

The sample is a random sample from a population, which is not an important assumption.

Thus, option (a) is incorrect.

Option (c) is incorrect because there are outliers in the sample.

Conclusion:

An important assumption for using the bootstrap method is that the sample distribution for the sample median must not be well approximated by the normal distribution.

The sampling distribution of the sample median does not follow a normal distribution.

Thus, the correct option is (b).

Reasons for the incorrect answers:

The sample is a random sample from a population, which is not an important assumption.

Thus, option (a) is incorrect.

Option (c) is incorrect because there are outliers in the sample.

Conclusion:

An important assumption for using the bootstrap method is that the sample distribution for the sample median must not be well approximated by the normal distribution.

asked 2021-02-12

Which of the following is true about sampling distributions?

-Shape of the sampling distribution is always the same shape as the population distribution, no matter what the sample size is.

-Sampling distributions are always nearly normal.

-Sampling distribution of the mean is always right skewed since means cannot be smaller than 0.

-Sampling distributions get closer to normality as the sample size increases.

-Shape of the sampling distribution is always the same shape as the population distribution, no matter what the sample size is.

-Sampling distributions are always nearly normal.

-Sampling distribution of the mean is always right skewed since means cannot be smaller than 0.

-Sampling distributions get closer to normality as the sample size increases.

asked 2020-12-07

Which of the following are possible examples of sampling distributions? (Select all that apply.)

mean trout lengths based on samples of size 5

average SAT score of a sample of high school students

average male height based on samples of size 30

heights of college students at a sampled universit

yall mean trout lengths in a sampled lake

mean trout lengths based on samples of size 5

average SAT score of a sample of high school students

average male height based on samples of size 30

heights of college students at a sampled universit

yall mean trout lengths in a sampled lake

asked 2021-03-09

Which of the following is true about the sampling distribution of means?

A. Shape of the sampling distribution of means is always the same shape as the population distribution, no matter what the sample size is.

B. Sampling distributions of means are always nearly normal.

C. Sampling distributions of means get closer to normality as the sample size increases.

D. Sampling distribution of the mean is always right skewed since means cannot be smaller than 0.

A. Shape of the sampling distribution of means is always the same shape as the population distribution, no matter what the sample size is.

B. Sampling distributions of means are always nearly normal.

C. Sampling distributions of means get closer to normality as the sample size increases.

D. Sampling distribution of the mean is always right skewed since means cannot be smaller than 0.

asked 2021-03-04

Which of the following statements about the sampling distribution of the sample mean is incorrect?

(a) The standard deviation of the sampling distribution will decrease as the sample size increases.

(b) The standard deviation of the sampling distribution is a measure of the variability of the sample mean among repeated samples.

(c) The sample mean is an unbiased estimator of the population mean.

(d) The sampling distribution shows how the sample mean will vary in repeated samples.

(e) The sampling distribution shows how the sample was distributed around the sample mean.

(a) The standard deviation of the sampling distribution will decrease as the sample size increases.

(b) The standard deviation of the sampling distribution is a measure of the variability of the sample mean among repeated samples.

(c) The sample mean is an unbiased estimator of the population mean.

(d) The sampling distribution shows how the sample mean will vary in repeated samples.

(e) The sampling distribution shows how the sample was distributed around the sample mean.

asked 2022-03-01

A random sample of 500 people were classified by their ages into 3 age-groups: 29 years and younger, 30 to 64 years, and 65 years and older. Each person from the sample was surveyed about which of 4 major brands of cell phone they used. Their responses were compiled and displayed in a 3-by-4 contingency table. A researcher will use the data to investigate whether there is an association between cell phone brand and age- group. Which of the following is the appropriate test for the investigation?

a. A one-sample t-test for a population mean

b. A two-sample t-test for a difference between means

c. A chi-square goodness-of-fit test

d. A chi-square test of homogeneity

e. A chi-square test of independence

a. A one-sample t-test for a population mean

b. A two-sample t-test for a difference between means

c. A chi-square goodness-of-fit test

d. A chi-square test of homogeneity

e. A chi-square test of independence

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