Exercise 3If we increase the number of replicates to 1000, then we will encounter a larger percentage of possible values for p at frequencies proportional totheir probabilities of occurrence. By plotting these replicates in a histogram, we can start to visualize the probability distribution of p. The codebelow provides an example with sample size n = 10. Alter the plot so that the color is red, the x-axis reads "Proportion of Heads", y-axis reads"Frequency", and the title (main) says "Distribution of Sample Proportions, n=10":Code Start Over1 values-c("H","T")2 phats-replicate(1000, sum(sample(values, 10, replace-TRUE)--"H")/10)3 hist(phots, xlab-"X label here",ylab-"y label here", main-"Put title here",col="orange")Exercise 4Besides plotting the distribution, we can also use simulations to estimate the expected value/mean or standard deviation of random variables.The output below computes the mean. Change it so that it computes the standard deviation (command=sd):CodeRun CodeStart Over1 volues-c("H","T")2 repeats-replicate(1000, sum(sample(values, 10, replace-TRUE)--"H")/10)3 mean(repeats)Run Code

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Exercise 3 If we increase the number of replicates to 1000, then we will encounter a larger percentage of possible values for at frequencies proportional to their probabilities of occurrence. By plotting these replicates in a histogram, we can start to visualize the probability distribution of p. The code below provides an example with sample size = 10. Alter the plot so that the color is red, the x-axis reads "Proportion of Heads", y-axis reads "Frequency", and the title (main) says "Distribution of Sample Proportions, n-10": Code Start Over 1 values-c("H","T") 2 phots-replicate(1000, sum(sample(values, 10, replace-TRUE)--"H")/10) 3 hist(phots, xlab-"x label here",ylab-"y label here",main-"Put title here",col-"orange") Run Code

Exercise 3 If we increase the number of replicates to 1000, then we will encounter a larger percentage of possible values for at frequencies proportional to their probabilities of occurrence. By plotting these replicates in a histogram, we can start to visualize the probability distribution of p. The code below provides an example with sample size = 10. Alter the plot so that the color is red, the x-axis reads "Proportion of Heads", y-axis reads "Frequency", and the title (main) says "Distribution of Sample Proportions, n-10": Code Start Over 1 values-c("H","T") 2 phots-replicate(1000, sum(sample(values, 10, replace-TRUE)--"H")/10) 3 hist(phots, xlab-"x label here",ylab-"y label here",main-"Put title here",col-"orange") Run Code

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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