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package org.statcato.statistics.inferential;
import org.statcato.statistics.*;
import org.statcato.utils.HelperFunctions;
/**
* A hypothesis test for 1 population proportion.
*
* @author Margaret Yau
* @version %I%, %G%
* @since 1.0
*/
public class HypothesisTest1Prop {
int n; // sample size
double p; // hypothesized proportion
double confidenceLevel; // confidence level
int testType; // type of test
/**
* Constructor.
*
* @param n sample size
* @param p hypothesized proportion
* @param confidenceLevel confidence level
* @param testType (as defined in {@link HypothesisTest})
*/
public HypothesisTest1Prop(int n, double p,
double confidenceLevel, int testType) {
this.n = n;
this.p = p;
this.confidenceLevel = confidenceLevel;
this.testType = testType;
}
/**
* Returns the test statistics for the given sample proportion pHat.
*
* z = (pHat - p) / sqrt(p * (1-p) / n)
*
* @param pHat hypothesized population proportion
* @return test statistic z score
*/
public double testStatistics(double pHat) {
return (pHat - p) / Math.sqrt(p * (1 - p) / n);
}
/**
* Returns the critical value corresponding to the given confidence
* level and type of test. Uses the z distribution.
*
* @return critical value
* @see HypothesisTest
*/
public String criticalValue() {
double alpha = 1 - confidenceLevel;
NormalProbabilityDistribution dist =
new NormalProbabilityDistribution(0, 1); // z distribution
if (testType == HypothesisTest.RIGHT_TAIL)
return HelperFunctions.formatFloat(
dist.inverseCumulativeProbability(1 - alpha), 3);
else if (testType == HypothesisTest.LEFT_TAIL)
return HelperFunctions.formatFloat(
dist.inverseCumulativeProbability(alpha), 3);
else // two tail
return
HelperFunctions.formatFloat(
dist.inverseCumulativeProbability(alpha / 2), 3) + ", " +
HelperFunctions.formatFloat(
dist.inverseCumulativeProbability(1 - alpha / 2), 3);
}
/**
* Returns the p-value corresponding to pHat in a z distribution.
*
* @param pHat sample proportion
* @return p-value
*/
public double pValue(double pHat) {
double ts = testStatistics(pHat);
NormalProbabilityDistribution dist =
new NormalProbabilityDistribution(0, 1); // z distribution
if (testType == HypothesisTest.LEFT_TAIL)
return dist.cumulativeProbability(ts);
else if (testType == HypothesisTest.RIGHT_TAIL)
return 1 - dist.cumulativeProbability(ts);
else { // two tail
double area = dist.cumulativeProbability(ts);
if (area > 0.5)
area = 1 - area;
return 2 * area;
}
}
}
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