# One Way ANOVA

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/*

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

Source of example data:
An Introduction to Computational Statitics by Robert I. Jennrich.
Page 199, example of regression on time for coins to reach bottom of fountains.

*/
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.data.DataType;
import edu.ucla.stat.SOCR.analyses.result.AnovaOneWayResult;

public class AnovaOneWayExample {
public static void main(String args[]) {
String[] group =
{"1","1","1","1","1","1", "2","2","2","2","2","2","2","2", "3","3","3","3","3"};
double[] time =
{93,67,77,92,97,62, 136,120,115,104,115,121,102,130, 198,217,209,221,190};

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

/*********************************************************************
then put the data into the Data Object.
append the predictor data using method "addPredictor".
append the response data using method "addResponse".
**********************************************************************/

data.addPredictor(group, DataType.FACTOR);
data.addResponse(time, DataType.QUANTITATIVE);

try {
AnovaOneWayResult result = data.modelAnovaOneWay();
if (result != null) {

// Getting the model's parameter estiamtes and statistics.
int dfCTotal = result.getDFTotal();
int dfModel = result.getDFModel();
int dfError = result.getDFError();

double rssTotal = result.getRSSTotal();
double rssModel = result.getRSSModel();
double rssError = result.getRSSError();

double mssModel = result.getMSSModel();
double mssError = result.getMSSError();

double fValue = result.getFValue();
String pValue = result.getPValue();

double[] residuals = result.getResiduals();
double[] predicted = result.getPredicted();

// residuals after being sorted ascendantly.
double[] sortedResiduals = result.getSortedResiduals();

// sortedResiduals after being standardized.
double[] sortedStandardizedResiduals =
result.getSortedStandardizedResiduals();

// the original index of sortedResiduals, stored as integer array.
int[] sortedResidualsIndex = result.getSortedResidualsIndex();

// the normal quantiles of sortedResiduals.
double[] sortedNormalQuantiles = result.getSortedNormalQuantiles();

// sortedNormalQuantiles after being standardized.
double[] sortedStandardizedNormalQuantiles =
result.getSortedStandardizedNormalQuantiles();

System.out.println("dfCTotal = " + dfCTotal);
System.out.println("dfModel = " + dfModel);
System.out.println("dfError = " + dfError);

System.out.println("rssTotal = " + rssTotal);
System.out.println("rssModel = " + rssModel);
System.out.println("rssError = " + rssError);

System.out.println("mssModel = " + mssModel);
System.out.println("mssError = " + mssError);

System.out.println("fValue = " + fValue);
System.out.println("pValue = " + pValue);

for (int i = 0; i < residuals.length; i++) {
System.out.println("residuals["+i+"] = " + residuals[i]);
}

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


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