Data Science with Java – Part 4 : Testing Hypothesis with the inference package

To test if a certain hypothesis is likely to be true we can take advantage of the Apache commons math inference package.

Considering the tests included in the package is a good opportunity to learn more about statistics and probability theory.

Let´s consider the following binomial test about flipping a coin:

		BinomialTest binomialTest = new BinomialTest();

		double nullHypothesis = 0.5; //fair coin
		int numberOfSuccesses = 9; //number of heads (biased coin)
		
		//Two sided = Represents a right-sided test. H0: p ≤ p0, H1: p > p0.
		AlternativeHypothesis alternativeHypothesis = AlternativeHypothesis.TWO_SIDED;
		int numberOfTrials = 10;

		// Returns the observed significance level, or p-value, associated with
		// a Binomial test.
		double significanceLevel = binomialTest.binomialTest(numberOfTrials, numberOfSuccesses, nullHypothesis,
				alternativeHypothesis);

		double alpha = 0.03; //significance level of the test
		
		// Returns whether the null hypothesis can be rejected with the given
		// confidence level.
		//true if signficanceLevel < alpha
		boolean rejected = binomialTest.binomialTest(numberOfTrials, numberOfSuccesses, nullHypothesis,
				alternativeHypothesis, alpha);

		System.out.println("The significance level is " + significanceLevel);
		System.out.println("Can we reject the null hypothesis?" + rejected);

 

The result that we get is:

The significance level is 0.021484375000000003
Can we reject the null hypothesis?true

The significance level is lower that the expected value alpha; it means that we can discard the test.

In the next posts I will write about the ChiSquare and KolmogorovSmirnov tests too. Stay tuned! 🙂