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 s0 or Ts0. Test client. The test client takes two command-line arguments n and T and prints the relevant statistics for T computational experiments on n-by-n grid.
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 s0 or Ts0. Test client. The test client takes two command-line arguments n and T and prints the relevant statistics for T computational experiments on n-by-n grid.
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
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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.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F88167701-6d3f-46b8-9f75-5ab21a2347bf%2Fff3dbf24-eca6-4775-8f34-62c6998c954c%2Fii5uhv_processed.png&w=3840&q=75)
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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