List of anovaTest() Examples

Examples of anovaTest()

org.apache.commons.math.stat.inference.OneWayAnova.anovaTest()
Performs an ANOVA test, evaluating the null hypothesis that there is no difference among the means of the data categories.
Preconditions:
- The categoryData Collection must contain double[] arrays.
- There must be at least two double[] arrays in the categoryData collection and each of these arrays must contain at least two values.
- alpha must be strictly greater than 0 and less than or equal to 0.5.
@param categoryData Collection of double[]arrays each containing data for one category @param alpha significance level of the test @return true if the null hypothesis can be rejected withconfidence 1 - alpha @throws IllegalArgumentException if the preconditions are not met @throws MathException if the statistic can not be computed do to aconvergence or other numerical error.
org.apache.commons.math.stat.inference.OneWayAnovaImpl.anovaTest()
{@inheritDoc}
This implementation uses the {@link org.apache.commons.math.distribution.FDistribution commons-math F Distribution implementation} to estimate the exactp-value, using the formula
```
 p = 1 - cumulativeProbability(F)
```
where F is the F value and cumulativeProbability is the commons-math implementation of the F distribution.

True is returned iff the estimated p-value is less than alpha.

Examples of org.apache.commons.math.stat.inference.OneWayAnova.anovaTest()

      assertEquals("2.91", String.format("%2.2f", fValue));


      double pValue = anova.anovaPValue(bins);
      assertEquals("0.000002", String.format("%1.6f", pValue));


      boolean rejectNullHypothesis = anova.anovaTest(bins, 0.05);
      assertTrue(rejectNullHypothesis);
    } catch (MathException e) {
      System.err.println(e.getMessage());
      fail();
    } catch (Exception e) {

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Examples of org.apache.commons.math.stat.inference.OneWayAnova.anovaTest()

      // 0.002398777329392865
      double pValue = anova.anovaPValue(data);
      assertEquals("0.002", String.format("%1.3f", pValue));


      // alpha value can be 0 < alpha <= 0.5
      boolean rejectNullHypothesis = anova.anovaTest(data, 0.1);
      assertTrue(rejectNullHypothesis);
    } catch (MathException e) {
      System.err.println(e.getMessage());
      fail();
    }

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Examples of org.apache.commons.math.stat.inference.OneWayAnovaImpl.anovaTest()

      assertEquals("2.91", String.format("%2.2f", fValue));


      double pValue = anova.anovaPValue(bins);
      assertEquals("0.000002", String.format("%1.6f", pValue));


      boolean rejectNullHypothesis = anova.anovaTest(bins, 0.05);
      assertTrue(rejectNullHypothesis);
    } catch (MathException e) {
      System.err.println(e.getMessage());
      fail();
    } catch (Exception e) {

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Examples of org.apache.commons.math.stat.inference.OneWayAnovaImpl.anovaTest()

      // 0.002398777329392865
      double pValue = anova.anovaPValue(data);
      assertEquals("0.002", String.format("%1.3f", pValue));


      // alpha value can be 0 < alpha <= 0.5
      boolean rejectNullHypothesis = anova.anovaTest(data, 0.1);
      assertTrue(rejectNullHypothesis);
    } catch (MathException e) {
      System.err.println(e.getMessage());
      fail();
    }

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