import static java.lang.System.out;

import java.util.*;

 

import javastat.*;

import javastat.inference.onesample.*;

import static javastat.util.Argument.*;

import static javastat.util.Output.*;

import javastat.util.*;

 

/**

 *

 * <p>Example: class OneSampMeanTTest.</p>

 * <p>Data Source: Anderson, D. R., Sweeney, D. J. and Williams, T. A. (2001).

 *    Contemporary Business Statistics with Microsoft Excel. South-Western,

 *    p. 354. </p>

 */

 

public class OneSampMeanTTestExample

{

 

    public static void main(String arg[])

    {

        double[] testdata = {7, 8, 10, 8, 6, 9, 6, 7, 7, 8, 9, 8};

        DataManager dm = new DataManager();

 

        OneSampMeanTTest testclass1 =

new OneSampMeanTTest(0.05, 7, "greater", testdata);

        double testStatistic = testclass1.testStatistic;

        double pValue = testclass1.pValue;

        double lowerBound = testclass1.confidenceInterval[0];

        double upperBound = testclass1.confidenceInterval[1];

 

        OneSampMeanTTest testclass2 = new OneSampMeanTTest();

        double[] confidenceInterval = testclass2.confidenceInterval(0.05,

                testdata);

        testStatistic = testclass2.testStatistic(7, testdata);

        pValue = testclass2.pValue(7, "equal", testdata);

 

        Hashtable argument1 = new Hashtable();

        argument1.put(NULL_VALUE, 7);

        argument1.put(SIDE, "greater");

        argument1.put(ALPHA, 0.05);

        StatisticalAnalysis testclass3 = new OneSampMeanTTest(argument1,

                testdata).statisticalAnalysis;

        testStatistic = (Double) testclass3.output.get(TEST_STATISTIC);

        pValue = (Double) testclass3.output.get(PVALUE);

        confidenceInterval = (double[]) testclass3.output.get(

                CONFIDENCE_INTERVAL);

        lowerBound = confidenceInterval[0];

        upperBound = confidenceInterval[1];

 

        Hashtable argument2 = new Hashtable();

        OneSampMeanTTest testclass4 =

new OneSampMeanTTest(argument2, null);

        argument2.put(ALPHA, 0.05);

        confidenceInterval = testclass4.

confidenceInterval(argument2, testdata);

        argument2.put(NULL_VALUE, 7);

        testStatistic = testclass4.testStatistic(argument2, testdata);

        argument2.put(SIDE, "equal");

        pValue = testclass4.pValue(argument2, testdata);

    }

 

}

 

Results:

The test statistic based on non-null constructor         =  2.138

The p-value based on non-null constructor             =  0.028

The confidence interval based on non-null constructor   = [6.978 , 8.522]

 

{POINT_ESTIMATE_SE=0.351, TEST_STATISTIC=2.138,

POINT_ESTIMATE=7.75, CONFIDENCE_INTERVAL=[D@12ac982,

PVALUE=0.0279, DEGREE_OF_FREEDOM=11.0}

 

Description: the test statistic;

Classes: all classes in packages nonparametric, onesample, twosamples and

survival.inference, ChisqTest, OneWayANOVA, StatisticalInferenceTemplate,

 LinearRegression, CoxRegression

 

The test statistic based on null constructor             =  2.138

The p-value based on null constructor                 =  0.056

The confidence interval based on null constructor       = [6.978 , 8.522]

 

{TEST_STATISTIC=2.138, CONFIDENCE_INTERVAL=[D@1389e4,

PVALUE=0.0558}

 

See also:

Population Mean: Small Sample Case,

Tests about a Population Mean: Small Sample Case