Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN: 9780133594140
Author: James Kurose, Keith Ross
Publisher: PEARSON
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To perform a series of computational experiments, create a data type PercolationStats with the following API:
public class PercolationStats {
// perform independent trials on an n-by-n grid
public PercolationStats(int n, int trials)
// sample mean of percolation threshold
public double mean()
// sample standard deviation of percolation threshold
public double stddev()
// low endpoint of 95% confidence interval
public double confidenceLow()
// high endpoint of 95% confidence interval
public double confidenceHigh()
// test client (see below)
public static void main(String[] args)
}
The constructor takes two arguments n and T, and perform T independent computational experiments (discussed above) on an n-by-n grid. Using this experimental data, it calculates the mean,
standard deviation, and the 95% confidence interval for the percolation threshold.
Standard libraries. Use stdRandom
to generate random numbers; use stdStats
to compute the sample mean and standard deviation; use stopwatch
to measure the running time.
Corner cases. Throw an 1llegalArgumentException in the constructor if either n < 0 or T<0.
Test client. The test client takes two command-line arguments n and T and prints the relevant statistics for T computational experiments on an n-by-n grid.
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Transcribed Image Text:To perform a series of computational experiments, create a data type PercolationStats with the following API: public class PercolationStats { // perform independent trials on an n-by-n grid public PercolationStats(int n, int trials) // sample mean of percolation threshold public double mean() // sample standard deviation of percolation threshold public double stddev() // low endpoint of 95% confidence interval public double confidenceLow() // high endpoint of 95% confidence interval public double confidenceHigh() // test client (see below) public static void main(String[] args) } The constructor takes two arguments n and T, and perform T independent computational experiments (discussed above) on an n-by-n grid. Using this experimental data, it calculates the mean, standard deviation, and the 95% confidence interval for the percolation threshold. Standard libraries. Use stdRandom to generate random numbers; use stdStats to compute the sample mean and standard deviation; use stopwatch to measure the running time. Corner cases. Throw an 1llegalArgumentException in the constructor if either n < 0 or T<0. Test client. The test client takes two command-line arguments n and T and prints the relevant statistics for T computational experiments on an n-by-n grid.
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