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= In introductory statistical courses, you have learned how to test or estimate proportions. This is implemented by prop.test in R. Read the help file of prop.test function and understand the usage of this function. Suppose X1,..., X 20 is a random sample from Bernoulli(p 0.6) distribution. (Note: You can use rbinom(n,1,p) to generate this random sample, n = 20 in this case). Construct a 90% confidence in- terval for the parameter p using the prop.test function. Use a Monte Carlo method to obtain an empirical estimate of the confidence level and check if it is close to the nominal level 90%.

= In introductory statistical courses, you have learned how to test or estimate proportions. This is implemented by prop.test in R. Read the help file of prop.test function and understand the usage of this function. Suppose X1,..., X 20 is a random sample from Bernoulli(p 0.6) distribution. (Note: You can use rbinom(n,1,p) to generate this random sample, n = 20 in this case). Construct a 90% confidence in- terval for the parameter p using the prop.test function. Use a Monte Carlo method to obtain an empirical estimate of the confidence level and check if it is close to the nominal level 90%.

C++ for Engineers and Scientists
C++ for Engineers and Scientists
4th Edition
ISBN:9781133187844
Author:Bronson, Gary J.
Publisher:Bronson, Gary J.
Chapter5: Repetition Statements
Section5.5: A Closer Look: Loop Programming Techniques
Problem 12E: (Program) Write a program that tests the effectiveness of the rand() library function. Start by...
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= In introductory statistical courses, you have learned how to test or estimate proportions. This is implemented by prop.test in R. Read the help file of prop.test function and understand the usage of this function. Suppose X1,..., X 20 is a random sample from Bernoulli(p 0.6) distribution. (Note: You can use rbinom(n,1,p) to generate this random sample, n = 20 in this case). Construct a 90% confidence in- terval for the parameter p using the prop.test function. Use a Monte Carlo method to obtain an empirical estimate of the confidence level and check if it is close to the nominal level 90%.
Transcribed Image Text:= In introductory statistical courses, you have learned how to test or estimate proportions. This is implemented by prop.test in R. Read the help file of prop.test function and understand the usage of this function. Suppose X1,..., X 20 is a random sample from Bernoulli(p 0.6) distribution. (Note: You can use rbinom(n,1,p) to generate this random sample, n = 20 in this case). Construct a 90% confidence in- terval for the parameter p using the prop.test function. Use a Monte Carlo method to obtain an empirical estimate of the confidence level and check if it is close to the nominal level 90%.
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