Package org.moeaframework.util.statistics

Class TwoSampleTTest

java.lang.Object
org.moeaframework.util.statistics.IntervalRatioStatisticalTest
org.moeaframework.util.statistics.TwoSampleTTest
All Implemented Interfaces:
StatisticalTest
public class TwoSampleTTest extends IntervalRatioStatisticalTest
The Two-Sample t test determines if the mean of two populations are different. The independent flag in the constructor is used to choose between the unpaired (independent) and paired (dependent) test.
  • Null Hypothesis: The two population means are equal.
  • Alternative Hypothesis: The two population means are not equal.

Assumptions:

  1. Samples are randomly selected from the corresponding population
  2. The distribution of the underlying populations is normal

References:

  1. Sheskin, D.J. "Handbook of Parametric and Nonparametric Statistical Procedures, Third Edition." Chapman & Hall/CRC. 2004.

  • Constructor Details

    • TwoSampleTTest

      public TwoSampleTTest(boolean independent)
      Constructs a two sample T test.
      Parameters:
      independent - uses the unpaired T test if true; the paired T test if false

  • Method Details

    • add

      public void add(double value, int group)
      Description copied from class: IntervalRatioStatisticalTest
      Adds a new observation with the specified value and group.
      Overrides:
      add in class IntervalRatioStatisticalTest
      Parameters:
      value - the value of the new observation
      group - the group to which the new observation belongs

    • addAll

      public void addAll(double[] values, int group)
      Description copied from class: IntervalRatioStatisticalTest
      Adds several new observations to the specified group.
      Overrides:
      addAll in class IntervalRatioStatisticalTest
      Parameters:
      values - the values of the new observations
      group - the group to which the new observations belong

    • test

      public boolean test(double alpha)
      Returns true if the null hypothesis is rejected; false otherwise. The meaning of the null hypothesis and alternative hypothesis depends on the specific test.

      The prespecified level of confidence, alpha, can be used for either one-tailed or two-tailed (directional or non-directional) distributions, depending on the specific test. Some tests may only support specific values for alpha.

      Parameters:
      alpha - the prespecified level of confidence
      Returns:
      true if the null hypothesis is rejected; false otherwise
      See Also:
      • TestUtils.tTest(double[], double[], double)
      • TestUtils.pairedTTest(double[], double[], double)