Difference between revisions of "Two Independent Sample T-Test"

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Line 31: Line 31:
 
TwoIndependentTResult result =  
 
TwoIndependentTResult result =  
 
                         (TwoIndependentTResult) data.modelTwoIndependentT(methodA, methodB);
 
                         (TwoIndependentTResult) data.modelTwoIndependentT(methodA, methodB);
// modelTwoIndependentT:  
+
//* modelTwoIndependentT:  
                           order of first and second argumentd does NOT matter.
+
                           order of first and second argumentd does NOT matter. */
  
 
if (result != null) {
 
if (result != null) {

Revision as of 16:01, 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.TwoIndependentTResult;


public class TwoIndependentTExample {
	public static void main(String args[]) {
		double[] methodA = 
                       {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[] methodB = 
                       {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 {
			TwoIndependentTResult result = 
                        (TwoIndependentTResult) data.modelTwoIndependentT(methodA, methodB);
			//* modelTwoIndependentT: 
                           order of first and second argumentd does NOT matter. */

			if (result != null) {

				// Getting the model's parameter estiamtes and statistics.
				double meanX = result.getMeanX();
				double meanY = result.getMeanY();

				// sum of variance of x and variance of y.
				double sampleVar = result.getSampleVariance();

				int degreesFreedome = result.getDF();
				double tStat = result.getTStat();
				String pValue = result.getPValue();

				System.out.println("meanX = " + meanX);
				System.out.println("meanY = " + meanY);
				System.out.println("sampleVar = " + sampleVar);
				System.out.println("degreesFreedome = " + degreesFreedome);
				System.out.println("tStat = " + tStat);
				System.out.println("pValue = " + pValue);


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