Two Independent Sample T-Test - Revision history

Annie at 00:10, 22 January 2007

2007-01-22T00:10:06Z

IvoDinov at 05:49, 19 January 2007

2007-01-19T05:49:17Z

Annie at 21:01, 31 July 2006

2006-07-31T21:01:45Z

Annie at 21:01, 31 July 2006

2006-07-31T21:01:20Z

Annie at 20:59, 31 July 2006

2006-07-31T20:59:55Z

New page

<pre>/*

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);
}
}
}
</pre>

@@ Line 32: / Line 32: @@
                          (TwoIndependentTResult) data.modelTwoIndependentT(methodA, methodB);
 			//* modelTwoIndependentT:
-                            order of first and second argumentd does NOT matter. */
+                            order of first and second arguments does NOT matter. */
 			if (result != null) {

← Older revision		Revision as of 05:49, 19 January 2007
Line 62:		Line 62:
	}		}
	</pre>		</pre>
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		+	{{translate\|pageName=http://wiki.stat.ucla.edu/socr/index.php?title=Two_Independent_Sample_T-Test}}

@@ Line 3: / Line 3: @@
 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.
+Source of example data:
 */
@@ Line 15: / Line 17: @@
 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[] methodA =
-		double[] methodB = {80.02, 79.94, 79.98, 79.97, 79.97, 80.03, 79.95, 79.97};
+                       {79.98, 80.04, 80.02, 80.04, 80.03, 80.03,
 		// you'll need to instantiate a data instance first.
@@ Line 24: / Line 29: @@
 		// then use the following line to get the result.
 		try {
-			TwoIndependentTResult result = (TwoIndependentTResult) data.modelTwoIndependentT(methodA, methodB);
+			TwoIndependentTResult result =
-			// modelTwoIndependentT: order of first and second argumentd does NOT matter.
+                        (TwoIndependentTResult) data.modelTwoIndependentT(methodA, methodB);
 			if (result != null) {