One Way ANOVA

/*

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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