Kyran Hudson
2021-03-01
Answered

Explain whether the central limit theorem can be applied and assert that the sampling distributions of A and Bare approximately normal, if the sample sizes of A and Bare large.

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izboknil3

Answered 2021-03-02
Author has **99** answers

In general, the central limit theorem applies only to the sample mean.

In this case, A and Bare not sample means. Thus, the central limit theorem cannot be applied.

Therefore, people cannot assert that the sampling distributions of A and Bare approximately normal, if the sample sizes of A and Bare large.

In this case, A and Bare not sample means. Thus, the central limit theorem cannot be applied.

Therefore, people cannot assert that the sampling distributions of A and Bare approximately normal, if the sample sizes of A and Bare large.

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 2021-02-12

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 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 2020-10-28

Explain the statement ‘The main priority with sampling distributions is to get across the idea that estimates and other statistics change every time we do a new study’.

asked 2021-06-26

asked 2021-01-31

Critical Thinking Let x be a random variable representing the amount of sleep each adult in New York City got last night. Consider a sampling distribution of sample means $\stackrel{\u2015}{x}$ .

What value will the standard deviation${\sigma}_{\stackrel{\u2015}{x}}$ of the sampling distribution approach?

What value will the standard deviation