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Improved javadoc; changed confidence level to significance level. JIRA: MATH-1034. 

git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@1532638 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Phil Steitz 2013-10-16 04:29:31 +00:00
parent 9b1f983f71
commit e65901dcb8
2 changed files with 22 additions and 14 deletions
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20
src/main/java/org/apache/commons/math3/stat/inference/BinomialTest.java
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@ -51,8 +51,8 @@ public class BinomialTest {
* @param numberOfSuccesses number of successes observed
* @param probability assumed probability of a single trial under the null hypothesis
* @param alternativeHypothesis type of hypothesis being evaluated (one- or two-sided)
* @param confidenceLevel confidence level of the test
* @return true if the null hypothesis can be rejected with confidence {@code confidenceLevel}
* @param alpha significance level of the test
* @return true if the null hypothesis can be rejected with confidence {@code 1 - alpha}
* @throws NotPositiveException if {@code numberOfTrials} or {@code numberOfSuccesses} is negative
* @throws OutOfRangeException if {@code probability} is not between 0 and 1
* @throws MathIllegalArgumentException if {@code numberOfTrials} < {@code numberOfSuccesses} or
@ -60,9 +60,9 @@ public class BinomialTest {
* @see AlternativeHypothesis
*/
public boolean binomialTest(int numberOfTrials, int numberOfSuccesses, double probability,
AlternativeHypothesis alternativeHypothesis, double confidenceLevel) {
AlternativeHypothesis alternativeHypothesis, double alpha) {
double pValue = binomialTest(numberOfTrials, numberOfSuccesses, probability, alternativeHypothesis);
return pValue < 1 - confidenceLevel;
return pValue < alpha;
}
/**
@ -71,7 +71,15 @@ public class BinomialTest {
* associated with a <a href="http://en.wikipedia.org/wiki/Binomial_test"> Binomial test</a>.
* <p>
* The number returned is the smallest significance level at which one can reject the null hypothesis.
* The form of the hypothesis depends on {@code alternativeHypothesis}.
* The form of the hypothesis depends on {@code alternativeHypothesis}.</p>
* <p>
* The p-Value represents the likelihood of getting a result at least as extreme as the sample,
* given the provided {@code probability} of success on a single trial. For single-sided tests,
* this value can be directly derived from the Binomial distribution. For the two-sided test,
* the implementation works as follows: we start by looking at the most extreme cases
* (0 success and n success where n is the number of trials from the sample) and determine their likelihood.
* The lower value is added to the p-Value (if both values are equal, both are added). Then we continue with
* the next extreme value, until we added the value for the actual observed sample.</p>
* <p>
* <strong>Preconditions</strong>:
* <ul>
@ -79,7 +87,7 @@ public class BinomialTest {
* <li>Number of successes must be &ge; 0.</li>
* <li>Number of successes must be &le; number of trials.</li>
* <li>Probability must be &ge; 0 and &le; 1.</li>
* </ul>
* </ul></p>
*
* @param numberOfTrials number of trials performed
* @param numberOfSuccesses number of successes observed

16
src/test/java/org/apache/commons/math3/stat/inference/BinomialTestTest.java
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@ -67,15 +67,15 @@ public class BinomialTestTest {
@Test
public void testBinomialTestAcceptReject() {
double confidenceLevel95 = 0.95;
double confidenceLevel99 = 0.99;
double alpha05 = 0.05;
double alpha01 = 0.01;
Assert.assertTrue(testStatistic.binomialTest(trials, successes, probability, AlternativeHypothesis.TWO_SIDED, confidenceLevel95));
Assert.assertTrue(testStatistic.binomialTest(trials, successes, probability, AlternativeHypothesis.GREATER_THAN, confidenceLevel95));
Assert.assertFalse(testStatistic.binomialTest(trials, successes, probability, AlternativeHypothesis.LESS_THAN, confidenceLevel95));
Assert.assertTrue(testStatistic.binomialTest(trials, successes, probability, AlternativeHypothesis.TWO_SIDED, alpha05));
Assert.assertTrue(testStatistic.binomialTest(trials, successes, probability, AlternativeHypothesis.GREATER_THAN, alpha05));
Assert.assertFalse(testStatistic.binomialTest(trials, successes, probability, AlternativeHypothesis.LESS_THAN, alpha05));
Assert.assertFalse(testStatistic.binomialTest(trials, successes, probability, AlternativeHypothesis.TWO_SIDED, confidenceLevel99));
Assert.assertFalse(testStatistic.binomialTest(trials, successes, probability, AlternativeHypothesis.GREATER_THAN, confidenceLevel99));
Assert.assertFalse(testStatistic.binomialTest(trials, successes, probability, AlternativeHypothesis.LESS_THAN, confidenceLevel95));
Assert.assertFalse(testStatistic.binomialTest(trials, successes, probability, AlternativeHypothesis.TWO_SIDED, alpha01));
Assert.assertFalse(testStatistic.binomialTest(trials, successes, probability, AlternativeHypothesis.GREATER_THAN, alpha01));
Assert.assertFalse(testStatistic.binomialTest(trials, successes, probability, AlternativeHypothesis.LESS_THAN, alpha05));
}
}