Difference between revisions of "Two Independent Sample Wilcoxon Test"

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Line 19: Line 19:
 
public static void main(String args[]) {
 
public static void main(String args[]) {
  
double[] methodA =  
+
double[] a =  
 
                 {79.98, 80.04, 80.02, 80.04, 80.03, 80.03,  
 
                 {79.98, 80.04, 80.02, 80.04, 80.03, 80.03,  
 
                 80.04, 79.97, 80.05, 80.03, 80.02, 80.00, 80.02};
 
                 80.04, 79.97, 80.05, 80.03, 80.02, 80.00, 80.02};
  
double[] methodB =  
+
double[] b =  
 
                 {80.02, 79.94, 79.98, 79.97, 79.97, 80.03, 79.95, 79.97};
 
                 {80.02, 79.94, 79.98, 79.97, 79.97, 80.03, 79.95, 79.97};
  
Line 33: Line 33:
 
try {
 
try {
 
TwoIndependentWilcoxonResult result =  
 
TwoIndependentWilcoxonResult result =  
                         (TwoIndependentWilcoxonResult)data.modelTwoIndependentWilcoxon(methodA, methodB);
+
                         (TwoIndependentWilcoxonResult)data.modelTwoIndependentWilcoxon(a,b);
 
+
                     
/* modelTwoIndependentWilcoxon:
+
                        if (result != null) {
                        order of first and second argumentd does NOT matter.*/
+
                // Getting the model's parameter estiamtes and statistics.
 
 
 
 
if (result != null) {
 
 
 
// Getting the model's parameter estiamtes and statistics.
 
 
double meanX = result.getMeanX();
 
double meanX = result.getMeanX();
 
double meanY = result.getMeanY();
 
double meanY = result.getMeanY();

Revision as of 16:12, 31 July 2006

/*

July 2006. Annie Che <chea@stat.ucla.edu>. UCLA Statistics.

Source of example data: 
Mathematical Statistics and Data Analysis, John Rice, Second Edition. 
Page 390, example A, determination of the laten heat of fusion of ice.

*/
package edu.ucla.stat.SOCR.analyses.example;

import java.util.HashMap;
import edu.ucla.stat.SOCR.analyses.data.Data;
import edu.ucla.stat.SOCR.analyses.result.TwoIndependentWilcoxonResult;


public class TwoIndependentWilcoxonExample {
	public static void main(String args[]) {

		double[] a = 
                {79.98, 80.04, 80.02, 80.04, 80.03, 80.03, 
                80.04, 79.97, 80.05, 80.03, 80.02, 80.00, 80.02};

		double[] b = 
                {80.02, 79.94, 79.98, 79.97, 79.97, 80.03, 79.95, 79.97};

		// you'll need to instantiate a data instance first.
		Data data = new Data();


		// then use the following line to get the result.
		try {
			TwoIndependentWilcoxonResult result = 
                        (TwoIndependentWilcoxonResult)data.modelTwoIndependentWilcoxon(a,b);
                       
                         if (result != null) {
		                // Getting the model's parameter estiamtes and statistics.
				double meanX = result.getMeanX();
				double meanY = result.getMeanY();
				System.out.println("meanX = " + meanX);
				System.out.println("meanY = " + meanY);
				double rankSumSmall = result.getRankSumSmallerGroup();
				double rankSumLarge = result.getRankSumLargerGroup();
				System.out.println("rankSumSmall = " + rankSumSmall);
				System.out.println("rankSumLarge = " + rankSumLarge);
				double uStatSmall = result.getUStatSmallerGroup();
				double uStatLarge = result.getUStatLargerGroup();
				System.out.println("uStatSmall = " + uStatSmall);
				System.out.println("uStatLarge = " + uStatLarge);


				double meanU = result.getMeanU();
				double varU = result.getVarianceU();
				System.out.println("meanU = " + meanU);
				System.out.println("varU = " + varU);

				double zScore = result.getZScore();
				String pValue = result.getPValue();
				boolean isLargeSample = result.isLargeSample();

				System.out.println("zScore = " + zScore);
				System.out.println("pValue = " + pValue);
				System.out.println("isLargeSample = " + isLargeSample);


			}
		} catch (Exception e) {
			System.out.println(e);
		}
	}
}