1.2.18 Variance for accumulator. Validate that the following code, which adds themethods var () and stddev () to Accumulator, computes both the mean and varianceof the numbers presented as arguments to addDataValue():public class Accumulator{}private double m;private double s;private int N;public void addDataValue (double x){}N++;S = s + 1.0 * (N-1) / N * (x - m) * (x - m);m = m + (x - m) / N;public double mean(){ return m; }public double var(){ return s/(N - 1); }public double stddev(){ return Math.sqrt(this.var()); }This implementation is less susceptible to roundoff error than the straightforward im-plementation based on saving the sum of the squares of the numbers.

The code given in the question is a valid implementation of the var() and stddev() methods for the…

1.2.18 Variance for accumulator. Validate that the following code, which adds the methods var () and stddev () to Accumulator, computes both the mean and variance of the numbers presented as arguments to addDataValue(): public class Accumulator { private double m; private double s; private int N; public void addDataValue (double x) { N++; 1.0 (N-1) / N * (x m) * (x

1.2.18 Variance for accumulator. Validate that the following code, which adds the methods var () and stddev () to Accumulator, computes both the mean and variance of the numbers presented as arguments to addDataValue(): public class Accumulator { private double m; private double s; private int N; public void addDataValue (double x) { N++; 1.0 (N-1) / N * (x m) * (x

C++ Programming: From Problem Analysis to Program Design

8th Edition

ISBN:9781337102087

Author:D. S. Malik

Publisher:D. S. Malik

Chapter15: Recursion

Section: Chapter Questions

Problem 8SA

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Validate that the following code, which adds themethods var() and stddev() to Accumulator, computes both the mean and varianceof the numbers presented as arguments to addDataValue():public class Accumulator{ private double m; private double s; private int N; public void addDataValue(double x) { N++; s = s + 1.0 * (N-1) / N * (x - m) * (x - m); m = m + (x - m) / N; } public double mean() { return m; } public double var() { return s/(N - 1); } public double stddev() { return Math.sqrt(this.var()); }}This implementation is less susceptible to roundoff error than the straightforward implementation based on saving the sum of the squares of the number
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