Class T


  • public class T
    extends HypothesisTest
    Student's t-test tests for the equality of means, for the one-sample case, against a hypothetical mean, and for two-sample case, of two populations.

    Welch's t-test is an adaptation of Student's t-test intended for use with two samples having possibly unequal variances.

    The R equivalent function is t.test.

    See Also:
    • Constructor Summary

      Constructors 
      Constructor Description
      T​(double[] sample, double mu)
      Construct a one-sample location test of whether the mean of a normally distributed population has a value specified in a null hypothesis.
      T​(double[] sample1, double[] sample2)
      Construct Welch's t-test, an adaptation of Student's t-test, for the use with two samples having possibly unequal variances.
      T​(double[] sample1, double[] sample2, boolean isEqualVar, double mu)
      Construct a two sample location test of the null hypothesis that the means of two normally distributed populations are equal.
      T​(double[] sample1, double[] sample2, double mu)
      Construct Welch's t-test, an adaptation of Student's t-test, for the use with two samples having possibly unequal variances.
    • Constructor Detail

      • T

        public T​(double[] sample,
                 double mu)
        Construct a one-sample location test of whether the mean of a normally distributed population has a value specified in a null hypothesis.
        Parameters:
        sample - a sample
        mu - the hypothetical mean in the null hypothesis
      • T

        public T​(double[] sample1,
                 double[] sample2)
        Construct Welch's t-test, an adaptation of Student's t-test, for the use with two samples having possibly unequal variances.
        Parameters:
        sample1 - sample 1
        sample2 - sample 2
      • T

        public T​(double[] sample1,
                 double[] sample2,
                 double mu)
        Construct Welch's t-test, an adaptation of Student's t-test, for the use with two samples having possibly unequal variances.
        Parameters:
        sample1 - sample 1
        sample2 - sample 2
        mu - the hypothetical mean-difference in the null hypothesis
      • T

        public T​(double[] sample1,
                 double[] sample2,
                 boolean isEqualVar,
                 double mu)
        Construct a two sample location test of the null hypothesis that the means of two normally distributed populations are equal.
        Parameters:
        sample1 - sample 1
        sample2 - sample 2
        isEqualVar - true if we assume the variances of the two samples are equal; false otherwise
        mu - the hypothetical mean-difference in the null hypothesis. The default value is 0.
    • Method Detail

      • rightOneSidedPvalue

        public double rightOneSidedPvalue()
        Get the right, one-sided p-value.
        Returns:
        the right, one-sided p-value.
      • leftOneSidedPvalue

        public double leftOneSidedPvalue()
        Get the left, one-sided p-value.
        Returns:
        the left, one-sided p-value.
      • confidenceInterval

        public double[] confidenceInterval​(double confidence)
        Get the confidence interval.
        Parameters:
        confidence - the confidence level, e.g., for a 2-sided 95% confidence interval, we use 0.975 because 1 - 0.95 = 2 * (1 - 0.025)
        Returns:
        the left and right interval values
      • rightConfidenceInterval

        public double rightConfidenceInterval​(double confidence)
        Get the one sided right confidence interval, [a, ∞)
        Parameters:
        confidence - the confidence level, e.g., 0.95 for 95% confidence interval
        Returns:
        the left interval value
      • leftConfidenceInterval

        public double leftConfidenceInterval​(double confidence)
        Get the one sided left confidence interval, [0, a]
        Parameters:
        confidence - the confidence level, e.g., 0.95 for 95% confidence interval
        Returns:
        the right interval value
      • df

        public double df()
        Get the degree of freedom.
        Returns:
        the degree of freedom
      • mean1

        public double mean1()
        Get the mean of the first sample.
        Returns:
        the mean of the first sample
      • mean2

        public double mean2()
        Get the mean of the second sample.
        Returns:
        the mean of the second sample