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Q2) EXAMPLE WIT RMAL RANDUM VARIABLE: turn in the printout Suppose the random variable "height" has a normal distribution with mean 67 and variance of 14. Use the rnorm() function to draw three random samples from this population with the sizes 10, 1000 and 1000,000 respectively. Calculate the sample mean in each case and show that as n increases the sample mean approaches the true population mean. Reminder: The "RNORMAL" function in R: RNORMAL (# sample size, mean = # population mean: sd = # population standard deviation)

Q2) EXAMPLE WIT RMAL RANDUM VARIABLE: turn in the printout Suppose the random variable "height" has a normal distribution with mean 67 and variance of 14. Use the rnorm() function to draw three random samples from this population with the sizes 10, 1000 and 1000,000 respectively. Calculate the sample mean in each case and show that as n increases the sample mean approaches the true population mean. Reminder: The "RNORMAL" function in R: RNORMAL (# sample size, mean = # population mean: sd = # population standard deviation)

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.4: Distributions Of Data
Problem 22PFA
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Please solve the question with R studio or show calculation steps, thank you. Do not randomly write wrong answers if don't know how to solve.
Q2) EXAMPLE WITH A NORMAL RANDOM VARIABLE: turn in the printout Suppose the random variable "height" has a normal distribution with mean 67 and variance of 14. Use the rnorm() function to draw three random samples from this population with the sizes 10, 1000 and 1000,000 respectively. Calculate the sample mean in each case and show that as n increases the sample mean approaches the true population mean. Reminder: The "RNORMAL" function in R: RNORMAL ( # sample size, mean = # population mean; sd = # population standard deviation) Use R to illustrate the central limit theorem. The "central limit theorem" states that as n increases X-E(X) V(X) approaches standard normal
Transcribed Image Text:Q2) EXAMPLE WITH A NORMAL RANDOM VARIABLE: turn in the printout Suppose the random variable "height" has a normal distribution with mean 67 and variance of 14. Use the rnorm() function to draw three random samples from this population with the sizes 10, 1000 and 1000,000 respectively. Calculate the sample mean in each case and show that as n increases the sample mean approaches the true population mean. Reminder: The "RNORMAL" function in R: RNORMAL ( # sample size, mean = # population mean; sd = # population standard deviation) Use R to illustrate the central limit theorem. The "central limit theorem" states that as n increases X-E(X) V(X) approaches standard normal
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