## Uses of Class
org.apache.commons.math3.exception.NotPositiveException

- Packages that use NotPositiveException
  Package | Description
  --- | ---
  org.apache.commons.math3.distribution | Implementations of common discrete and continuous distributions.
  org.apache.commons.math3.stat.inference | Classes providing hypothesis testing and confidence interval construction.

- - ### Uses of NotPositiveException in org.apache.commons.math3.distribution

    Constructors in org.apache.commons.math3.distribution that throw NotPositiveException
    Constructor and Description
    `HypergeometricDistribution(int populationSize, int numberOfSuccesses, int sampleSize)` Construct a new hypergeometric distribution with the specified population size, number of successes in the population, and sample size.

  - ### Uses of NotPositiveException in org.apache.commons.math3.stat.inference

    Methods in org.apache.commons.math3.stat.inference that throw NotPositiveException
    Modifier and Type | Method and Description
    --- | ---
    `double` | ChiSquareTest.`chiSquare(double[] expected, long[] observed)` Computes the Chi-Square statistic comparing `observed` and `expected` frequency counts.
    `static double` | TestUtils.`chiSquare(double[] expected, long[] observed)`
    `double` | ChiSquareTest.`chiSquare(long[][] counts)` Computes the Chi-Square statistic associated with a chi-square test of independence based on the input `counts` array, viewed as a two-way table.
    `static double` | TestUtils.`chiSquare(long[][] counts)`
    `double` | ChiSquareTest.`chiSquareDataSetsComparison(long[] observed1, long[] observed2)` Computes a Chi-Square two sample test statistic comparing bin frequency counts in `observed1` and `observed2`.
    `static double` | TestUtils.`chiSquareDataSetsComparison(long[] observed1, long[] observed2)`
    `double` | ChiSquareTest.`chiSquareTest(double[] expected, long[] observed)` Returns the observed significance level, or p-value, associated with a Chi-square goodness of fit test comparing the `observed` frequency counts to those in the `expected` array.
    `static double` | TestUtils.`chiSquareTest(double[] expected, long[] observed)`
    `boolean` | ChiSquareTest.`chiSquareTest(double[] expected, long[] observed, double alpha)` Performs a Chi-square goodness of fit test evaluating the null hypothesis that the observed counts conform to the frequency distribution described by the expected counts, with significance level `alpha`.
    `static boolean` | TestUtils.`chiSquareTest(double[] expected, long[] observed, double alpha)`
    `double` | ChiSquareTest.`chiSquareTest(long[][] counts)` Returns the observed significance level, or p-value, associated with a chi-square test of independence based on the input `counts` array, viewed as a two-way table.
    `static double` | TestUtils.`chiSquareTest(long[][] counts)`
    `boolean` | ChiSquareTest.`chiSquareTest(long[][] counts, double alpha)` Performs a chi-square test of independence evaluating the null hypothesis that the classifications represented by the counts in the columns of the input 2-way table are independent of the rows, with significance level `alpha`.
    `static boolean` | TestUtils.`chiSquareTest(long[][] counts, double alpha)`
    `double` | ChiSquareTest.`chiSquareTestDataSetsComparison(long[] observed1, long[] observed2)` Returns the observed significance level, or p-value, associated with a Chi-Square two sample test comparing bin frequency counts in `observed1` and `observed2`.
    `static double` | TestUtils.`chiSquareTestDataSetsComparison(long[] observed1, long[] observed2)`
    `boolean` | ChiSquareTest.`chiSquareTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)` Performs a Chi-Square two sample test comparing two binned data sets.
    `static boolean` | TestUtils.`chiSquareTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)`

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