The central limit theorem implies which of the following: a. The averages of many random samples (of a given sample size n) from the same population are approximately normally distributed, but only if the population is normally distributed. b. The averages of many random samples (of a given sample size n) from the same population are approximately normally distributed with mean μ and standard deviation σ / √n , but only if the population is normally distributed. c. The averages of many random samples (of a given sample size n) from the same population are approximately normally distributed, regardless of the shape of the population distribution, provided that n is sufficiently large. d. None of these choices are true.

The central limit theorem implies which of the following: a. The averages of many random samples (of a given sample size n) from the same population are approximately normally distributed, but only if the population is normally distributed. b. The averages of many random samples (of a given sample size n) from the same population are approximately normally distributed with mean μ and standard deviation σ / √n , but only if the population is normally distributed. c. The averages of many random samples (of a given sample size n) from the same population are approximately normally distributed, regardless of the shape of the population distribution, provided that n is sufficiently large. d. None of these choices are true.

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter10: Introduction To Simulation Modeling

Section10.2: Probability Distributions For Input Variables

Problem 2P: Use Excels functions (not @RISK) to generate 1000 random numbers from a normal distribution with...

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