Standard Normal Distribution (SND) – Java Program
Last Updated :
06 Feb, 2018
The standard normal distribution is a special case of the normal distribution. It occurs when a normal random variable has a mean of 0 and a standard deviation of 1. The normal random variable of a standard normal distribution is called a standard score or a z score.
A conversion from Normally distributed to Standard Normally distributed value occurs via the formula,
Z = (X - u) / s
where:
Z = value on the standard normal distribution
X = value on the original distribution
u = mean of the original distribution
s = standard deviation of the original distribution
Code –
import java.io.*;
import java.util.*;
class SDN {
public static void main(String[] args)
{
double Z, X, s, u;
X = 26 ;
u = 50 ;
s = 10 ;
Z = (X - u) / s;
System.out.println( "the Z-value obtained is: " + Z);
}
}
|
Output –
the Z-value obtained is: -2.4
Generating a Random Standard Normal Function – Using nextGaussian() in Java :
The nextGaussian() method is used to get the next random, Normally distributed double value with mean 0.0 and standard deviation 1.0.
Declaration :
public double nextGaussian()
Parameters :
NA
Return Value :
The method call returns the random, Normally distributed double value
with mean 0.0 and standard deviation 1.0.
Exception :
NA
The following example shows the usage of java.util.Random.nextGaussian():
Code –
import java.util.*;
public class NextGaussian {
public static void main(String[] args)
{
Random ran = new Random();
double nxt = ran.nextGaussian();
System.out.println( "The next Gaussian value generated is : " + nxt);
}
}
|
Output –
The next Gaussian value generated is : -0.24283691098606316
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