Homework Help is Here – Start Your Trial Now!
Math
Statistics
Why? What is the sampling distribution of x? = 86 and o = 2. Does the population need to be normally distributed for the sampling distribution of x to be approximately CITE Does the population need to be normally distributed for the sampling distribution of x to be approximately normally distributed? Why? OA. No. The central limit theorem states that regardless of the shape of the underlying population, the sampling distribution of x becomes approximately normal as the sample size, n, increases. OB. No. The central limit theorem states that only if the shape of the underlying population is normal or uniform does the sampling distribution of x become approximately normal as the sample size, n, increases. OC. Yes. The central limit theorem states that only for underlying populations that are normal is the shape of the sampling distribution of x normal, regardless of the sample size, n. OD. Yes. The central limit theorem states that the sampling variability of nonnormal populations will increase as the sample size increases,

Why? What is the sampling distribution of x? = 86 and o = 2. Does the population need to be normally distributed for the sampling distribution of x to be approximately CITE Does the population need to be normally distributed for the sampling distribution of x to be approximately normally distributed? Why? OA. No. The central limit theorem states that regardless of the shape of the underlying population, the sampling distribution of x becomes approximately normal as the sample size, n, increases. OB. No. The central limit theorem states that only if the shape of the underlying population is normal or uniform does the sampling distribution of x become approximately normal as the sample size, n, increases. OC. Yes. The central limit theorem states that only for underlying populations that are normal is the shape of the sampling distribution of x normal, regardless of the sample size, n. OD. Yes. The central limit theorem states that the sampling variability of nonnormal populations will increase as the sample size increases,

Algebra & Trigonometry with Analytic Geometry
Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter10: Sequences, Series, And Probability
Section10.8: Probability
Problem 10E
See similar textbooks
icon
Related questions
Question
G A simple random sample of size n=36 is obtained from a population that is skewed left with p=86 and o=2. Does the population need to be normally distributed for the sampling distribution of x to be approximately normally distributed? Why? What is the sampling distribution of x? Save Does the population need to be normally distributed for the sampling distribution of x to be approximately normally distributed? Why? A. No. The central limit theorem states that regardless of the shape of the underlying population, the sampling distribution of x becomes approximately normal as the sample size, n, increases. B. No. The central limit theorem states that only if the shape of the underlying population is normal or uniform does the sampling distribution of x become approximately normal as the sample size, n, increases. O C. Yes. The central limit theorem states that only for underlying populations that are normal is the shape of the sampling distribution of x normal, regardless of the sample size, n. O D. Yes. The central limit theorem states that the sampling variability of nonnormal populations will increase as the sample size increases.
Transcribed Image Text:G A simple random sample of size n=36 is obtained from a population that is skewed left with p=86 and o=2. Does the population need to be normally distributed for the sampling distribution of x to be approximately normally distributed? Why? What is the sampling distribution of x? Save Does the population need to be normally distributed for the sampling distribution of x to be approximately normally distributed? Why? A. No. The central limit theorem states that regardless of the shape of the underlying population, the sampling distribution of x becomes approximately normal as the sample size, n, increases. B. No. The central limit theorem states that only if the shape of the underlying population is normal or uniform does the sampling distribution of x become approximately normal as the sample size, n, increases. O C. Yes. The central limit theorem states that only for underlying populations that are normal is the shape of the sampling distribution of x normal, regardless of the sample size, n. O D. Yes. The central limit theorem states that the sampling variability of nonnormal populations will increase as the sample size increases.
Expert Solution
trending now

Trending now

This is a popular solution!

steps

Step by step

Solved in 3 steps

SEE SOLUTIONCheck out a sample Q&A here
Blurred answer
Follow-up Questions
Read through expert solutions to related follow-up questions below.
Follow-up Question
What is the sampling distribution of x? Select the correct choice below and fill in the answer boxes within your choice. (Type integers or decimals rounded to three decimal places as needed.) O A. The shape of the sampling distribution of x is unknown with μ- = X OB. The sampling distribution of x is uniform with μ-= OC. The sampling distribution of x is skewed left with = and o. = o- X OD. The sampling distribution of x is approximately normal with H and o and o- = X and o- = E
Transcribed Image Text:What is the sampling distribution of x? Select the correct choice below and fill in the answer boxes within your choice. (Type integers or decimals rounded to three decimal places as needed.) O A. The shape of the sampling distribution of x is unknown with μ- = X OB. The sampling distribution of x is uniform with μ-= OC. The sampling distribution of x is skewed left with = and o. = o- X OD. The sampling distribution of x is approximately normal with H and o and o- = X and o- = E
Solution
Bartleby Expert
SEE SOLUTION
Recommended textbooks for you
Algebra & Trigonometry with Analytic Geometry
Algebra & Trigonometry with Analytic Geometry
Algebra
ISBN:
9781133382119
Author:
Swokowski
Publisher:
Cengage
SEE MORE TEXTBOOKS