Return-Path: Delivered-To: apmail-jakarta-commons-dev-archive@www.apache.org Received: (qmail 12443 invoked from network); 11 Apr 2004 19:00:52 -0000 Received: from daedalus.apache.org (HELO mail.apache.org) (208.185.179.12) by minotaur-2.apache.org with SMTP; 11 Apr 2004 19:00:52 -0000 Received: (qmail 3087 invoked by uid 500); 11 Apr 2004 19:00:36 -0000 Delivered-To: apmail-jakarta-commons-dev-archive@jakarta.apache.org Received: (qmail 3047 invoked by uid 500); 11 Apr 2004 19:00:36 -0000 Mailing-List: contact commons-dev-help@jakarta.apache.org; run by ezmlm Precedence: bulk List-Unsubscribe: List-Subscribe: List-Help: List-Post: List-Id: "Jakarta Commons Developers List" Reply-To: "Jakarta Commons Developers List" Delivered-To: mailing list commons-dev@jakarta.apache.org Received: (qmail 3032 invoked by uid 500); 11 Apr 2004 19:00:36 -0000 Received: (qmail 3029 invoked from network); 11 Apr 2004 19:00:36 -0000 Received: from unknown (HELO minotaur.apache.org) (209.237.227.194) by daedalus.apache.org with SMTP; 11 Apr 2004 19:00:36 -0000 Received: (qmail 12398 invoked by uid 1718); 11 Apr 2004 19:00:45 -0000 Date: 11 Apr 2004 19:00:45 -0000 Message-ID: <20040411190045.12396.qmail@minotaur.apache.org> From: psteitz@apache.org To: jakarta-commons-cvs@apache.org Subject: cvs commit: jakarta-commons/math/src/java/org/apache/commons/math/stat BivariateRegression.java DescriptiveStatistics.java StatUtils.java TestStatistic.java X-Spam-Rating: daedalus.apache.org 1.6.2 0/1000/N X-Spam-Rating: minotaur-2.apache.org 1.6.2 0/1000/N psteitz 2004/04/11 12:00:45 Modified: math/src/java/org/apache/commons/math/linear RealMatrix.java RealMatrixImpl.java math/src/java/org/apache/commons/math/random RandomData.java RandomDataImpl.java math/src/java/org/apache/commons/math/stat BivariateRegression.java DescriptiveStatistics.java StatUtils.java TestStatistic.java Log: Javadoc. Fixed broken / malformed links. Revision Changes Path 1.15 +3 -4 jakarta-commons/math/src/java/org/apache/commons/math/linear/RealMatrix.java Index: RealMatrix.java =================================================================== RCS file: /home/cvs/jakarta-commons/math/src/java/org/apache/commons/math/linear/RealMatrix.java,v retrieving revision 1.14 retrieving revision 1.15 diff -u -r1.14 -r1.15 --- RealMatrix.java 8 Apr 2004 07:02:55 -0000 1.14 +++ RealMatrix.java 11 Apr 2004 19:00:45 -0000 1.15 @@ -107,9 +107,8 @@ void setData(double[][] data); /** - * Returns the maximum absolute row sum norm - * of the matrix. + * Returns the + * maximum absolute row sum norm of the matrix. * * @return norm */ 1.18 +9 -12 jakarta-commons/math/src/java/org/apache/commons/math/linear/RealMatrixImpl.java Index: RealMatrixImpl.java =================================================================== RCS file: /home/cvs/jakarta-commons/math/src/java/org/apache/commons/math/linear/RealMatrixImpl.java,v retrieving revision 1.17 retrieving revision 1.18 diff -u -r1.17 -r1.18 --- RealMatrixImpl.java 8 Apr 2004 20:46:01 -0000 1.17 +++ RealMatrixImpl.java 11 Apr 2004 19:00:45 -0000 1.18 @@ -21,13 +21,11 @@ /** * Implementation for RealMatrix using a double[][] array to store entries - * and LU decompostion to support linear system + * and + * LU decompostion to support linear system * solution and inverse. *

- * The LU decompostion is performed as needed, to support the - * following operations:

    + * The LU decompostion is performed as needed, to support the following operations:
      *
    • solve
    • *
    • isSingular
    • *
    • getDeterminant
    • @@ -617,14 +615,13 @@ } /** - * Computes a new LU decompostion for this matrix, - * storing the result for use by other methods. + * Computes a new + * + * LU decompostion for this matrix, storing the result for use by other methods. *

      * Implementation Note:
      - * Uses Crout's algortithm, - * with partial pivoting. + * Uses + * Crout's algortithm, with partial pivoting. *

      * Usage Note:
      * This method should rarely be invoked directly. Its only use is 1.9 +9 -17 jakarta-commons/math/src/java/org/apache/commons/math/random/RandomData.java Index: RandomData.java =================================================================== RCS file: /home/cvs/jakarta-commons/math/src/java/org/apache/commons/math/random/RandomData.java,v retrieving revision 1.8 retrieving revision 1.9 diff -u -r1.8 -r1.9 --- RandomData.java 21 Feb 2004 21:35:15 -0000 1.8 +++ RandomData.java 11 Apr 2004 19:00:45 -0000 1.9 @@ -107,8 +107,7 @@ * nextInt should be used instead of this method. *

      * Definition: - * + * * Secure Random Sequence *

      * Preconditions:

        @@ -131,8 +130,7 @@ * nextLong should be used instead of this method. *

        * Definition: - * + * * Secure Random Sequence *

        * Preconditions:

          @@ -152,8 +150,7 @@ * the given mean. *

          * Definition: - * + * * Poisson Distribution *

          * Preconditions:

            @@ -171,8 +168,7 @@ * and standard deviation. *

            * Definition: - * + * * Normal Distribution *

            * Preconditions:

              @@ -191,8 +187,7 @@ * with expected value = mean. *

              * Definition: - * + * * Exponential Distribution *

              * Preconditions:

                @@ -209,12 +204,10 @@ * (lower,upper) (i.e., endpoints excluded). *

                * Definition: - * + * * Uniform Distribution lower and * upper - lower are the - * + * * location and scale parameters, respectively. *

                * Preconditions:

                  @@ -258,8 +251,7 @@ * is without replacement; but if c contains identical * objects, the sample may include repeats. If all elements of * c are distinct, the resulting object array represents a - * + * * Simple Random Sample of size * k from the elements of c. *

                  1.13 +5 -6 jakarta-commons/math/src/java/org/apache/commons/math/random/RandomDataImpl.java Index: RandomDataImpl.java =================================================================== RCS file: /home/cvs/jakarta-commons/math/src/java/org/apache/commons/math/random/RandomDataImpl.java,v retrieving revision 1.12 retrieving revision 1.13 diff -u -r1.12 -r1.13 --- RandomDataImpl.java 21 Feb 2004 21:35:15 -0000 1.12 +++ RandomDataImpl.java 11 Apr 2004 19:00:45 -0000 1.13 @@ -30,7 +30,7 @@ * java.util.Random.SecureRandom instances to generate data. *

                  * Supports reseeding the underlying - * + * * PRNG. The SecurityProvider and Algorithm * used by the SecureRandom instance can also be reset. *

                  @@ -46,9 +46,8 @@ * one RandomDataImpl instance repeatedly. *

                • * The "secure" methods are *much* slower. These should be used only when - * a Secure Random - * Sequence is required.
                • + * a + * Secure Random Sequence is required. *
                • * When a new RandomDataImpl is created, the underlying random * number generators are not intialized. The first call to a @@ -462,7 +461,7 @@ /** * Uses a 2-cycle permutation shuffle to generate a random permutation. * The shuffling process is described - * + * * here. * @param n the population size. * @param k the number to choose. 1.16 +7 -7 jakarta-commons/math/src/java/org/apache/commons/math/stat/BivariateRegression.java Index: BivariateRegression.java =================================================================== RCS file: /home/cvs/jakarta-commons/math/src/java/org/apache/commons/math/stat/BivariateRegression.java,v retrieving revision 1.15 retrieving revision 1.16 diff -u -r1.15 -r1.16 --- BivariateRegression.java 21 Mar 2004 22:39:56 -0000 1.15 +++ BivariateRegression.java 11 Apr 2004 19:00:45 -0000 1.16 @@ -382,8 +382,8 @@ * Usage Note:
                  * The validity of this statistic depends on the assumption that the * observations included in the model are drawn from a - * Bivariate Normal Distribution. + * + * Bivariate Normal Distribution. * * @return half-width of 95% confidence interval for the slope estimate */ @@ -406,8 +406,8 @@ * Usage Note:
                  * The validity of this statistic depends on the assumption that the * observations included in the model are drawn from a - * Bivariate Normal Distribution. + * + * Bivariate Normal Distribution. *

                  * Preconditions:

                    *
                  • If there are fewer that three observations in the @@ -441,8 +441,8 @@ * Usage Note:
                    * The validity of this statistic depends on the assumption that the * observations included in the model are drawn from a - * Bivariate Normal Distribution. + * + * Bivariate Normal Distribution. *

                    * If there are fewer that three observations in the * model, or if there is no variation in x, this returns 1.6 +5 -4 jakarta-commons/math/src/java/org/apache/commons/math/stat/DescriptiveStatistics.java Index: DescriptiveStatistics.java =================================================================== RCS file: /home/cvs/jakarta-commons/math/src/java/org/apache/commons/math/stat/DescriptiveStatistics.java,v retrieving revision 1.5 retrieving revision 1.6 diff -u -r1.5 -r1.6 --- DescriptiveStatistics.java 21 Feb 2004 21:35:15 -0000 1.5 +++ DescriptiveStatistics.java 11 Apr 2004 19:00:45 -0000 1.6 @@ -228,9 +228,10 @@ /** * Returns an estimate for the pth percentile of the stored values. - * This estimate follows the interpolation-adjusted defintion presented - * here - *

                    + *

                    + * The implementation provided here follows the first estimation procedure presented + * here. + *

                    * Preconditions:

                      *
                    • 0 < p < 100 (otherwise an * IllegalArgumentException is thrown)
                    • 1.26 +36 -38 jakarta-commons/math/src/java/org/apache/commons/math/stat/StatUtils.java Index: StatUtils.java =================================================================== RCS file: /home/cvs/jakarta-commons/math/src/java/org/apache/commons/math/stat/StatUtils.java,v retrieving revision 1.25 retrieving revision 1.26 diff -u -r1.25 -r1.26 --- StatUtils.java 4 Mar 2004 04:25:09 -0000 1.25 +++ StatUtils.java 11 Apr 2004 19:00:45 -0000 1.26 @@ -27,9 +27,9 @@ import org.apache.commons.math.stat.univariate.summary.SumOfSquares; /** - * StatUtils provides easy static implementations of common double[] based + * StatUtils provides static implementations of common double[] based * statistical methods. These return a single result value or in some cases, as - * identified in the javadoc for each method, Double.NaN. + * identified in the javadoc for each method, Double.NaN. * @version $Revision$ $Date$ */ public final class StatUtils { @@ -70,7 +70,7 @@ /** * The sum of the values that have been added to Univariate. * @param values Is a double[] containing the values - * @return the sum of the values or Double.NaN if the array is empty + * @return the sum of the values or Double.NaN if the array is empty */ public static double sum(final double[] values) { return sum.evaluate(values); @@ -81,7 +81,7 @@ * @param values Is a double[] containing the values * @param begin processing at this point in the array * @param length the number of elements to include - * @return the sum of the values or Double.NaN if the array is empty + * @return the sum of the values or Double.NaN if the array is empty */ public static double sum( final double[] values, @@ -93,7 +93,7 @@ /** * Returns the sum of the squares of the available values. * @param values Is a double[] containing the values - * @return the sum of the squared values or Double.NaN if the array is empty + * @return the sum of the squared values or Double.NaN if the array is empty */ public static double sumSq(final double[] values) { return sumSq.evaluate(values); @@ -104,7 +104,7 @@ * @param values Is a double[] containing the values * @param begin processing at this point in the array * @param length the number of elements to include - * @return the sum of the squared values or Double.NaN if the array is empty + * @return the sum of the squared values or Double.NaN if the array is empty */ public static double sumSq( final double[] values, @@ -116,7 +116,7 @@ /** * Returns the product for this collection of values * @param values Is a double[] containing the values - * @return the product values or Double.NaN if the array is empty + * @return the product values or Double.NaN if the array is empty */ public static double product(final double[] values) { return prod.evaluate(values); @@ -127,7 +127,7 @@ * @param values Is a double[] containing the values * @param begin processing at this point in the array * @param length the number of elements to include - * @return the product values or Double.NaN if the array is empty + * @return the product values or Double.NaN if the array is empty */ public static double product( final double[] values, @@ -139,7 +139,7 @@ /** * Returns the sum of the natural logs for this collection of values * @param values Is a double[] containing the values - * @return the sumLog value or Double.NaN if the array is empty + * @return the sumLog value or Double.NaN if the array is empty */ public static double sumLog(final double[] values) { return sumLog.evaluate(values); @@ -150,7 +150,7 @@ * @param values Is a double[] containing the values * @param begin processing at this point in the array * @param length the number of elements to include - * @return the sumLog value or Double.NaN if the array is empty + * @return the sumLog value or Double.NaN if the array is empty */ public static double sumLog( final double[] values, @@ -160,22 +160,22 @@ } /** - * Returns the + * Returns the * arithmetic mean of the available values * @param values Is a double[] containing the values - * @return the mean of the values or Double.NaN if the array is empty + * @return the mean of the values or Double.NaN if the array is empty */ public static double mean(final double[] values) { return mean.evaluate(values); } /** - * Returns the + * Returns the * arithmetic mean of the available values * @param values Is a double[] containing the values * @param begin processing at this point in the array * @param length the number of elements to include - * @return the mean of the values or Double.NaN if the array is empty + * @return the mean of the values or Double.NaN if the array is empty */ public static double mean( final double[] values, @@ -186,15 +186,14 @@ /** * Returns the variance of the available values. This uses a corrected - * two pass algorithm of the following - * - * corrected two pass formula (14.1.8), and also referenced in:

                      + * two pass algorithm as described in: + *

                      * "Algorithms for Computing the Sample Variance: Analysis and * Recommendations", Chan, T.F., Golub, G.H., and LeVeque, R.J. - * 1983, American Statistician, vol. 37, pp. 242?247. + * 1983, American Statistician, vol. 37, pp. 242-247. * * @param values Is a double[] containing the values - * @return the result, Double.NaN if no values for an empty array + * @return the result, Double.NaN for an empty array * or 0.0 for a single value set. */ public static double variance(final double[] values) { @@ -203,17 +202,16 @@ /** * Returns the variance of the available values. This uses a corrected - * two pass algorithm of the following - * - * corrected two pass formula (14.1.8), and also referenced in:

                      + * two pass algorithm as described in: + *

                      * "Algorithms for Computing the Sample Variance: Analysis and * Recommendations", Chan, T.F., Golub, G.H., and LeVeque, R.J. - * 1983, American Statistician, vol. 37, pp. 242?247. + * 1983, American Statistician, vol. 37, pp. 242-247. * * @param values Is a double[] containing the values * @param begin processing at this point in the array * @param length the number of elements to include - * @return the result, Double.NaN if no values for an empty array + * @return the result, Double.NaN for an empty array * or 0.0 for a single value set. */ public static double variance( @@ -226,7 +224,7 @@ /** * Returns the maximum of the available values * @param values Is a double[] containing the values - * @return the maximum of the values or Double.NaN if the array is empty + * @return the maximum of the values or Double.NaN if the array is empty */ public static double max(final double[] values) { return max.evaluate(values); @@ -237,7 +235,7 @@ * @param values Is a double[] containing the values * @param begin processing at this point in the array * @param length the number of elements to include - * @return the maximum of the values or Double.NaN if the array is empty + * @return the maximum of the values or Double.NaN if the array is empty */ public static double max( final double[] values, @@ -249,7 +247,7 @@ /** * Returns the minimum of the available values * @param values Is a double[] containing the values - * @return the minimum of the values or Double.NaN if the array is empty + * @return the minimum of the values or Double.NaN if the array is empty */ public static double min(final double[] values) { return min.evaluate(values); @@ -260,7 +258,7 @@ * @param values Is a double[] containing the values * @param begin processing at this point in the array * @param length the number of elements to include - * @return the minimum of the values or Double.NaN if the array is empty + * @return the minimum of the values or Double.NaN if the array is empty */ public static double min( final double[] values, @@ -271,9 +269,10 @@ /** * Returns an estimate for the pth percentile of the stored values. - * This estimate follows the interpolation-adjusted defintion presented - * here - *

                      + *

                      + * The implementation provided here follows the first estimation procedure presented + * here. + *

                      * Preconditions:

                        *
                      • 0 < p < 100 (otherwise an * IllegalArgumentException is thrown)
                      • @@ -291,9 +290,10 @@ /** * Returns an estimate for the pth percentile of the stored values. - * This estimate follows the interpolation-adjusted defintion presented - * here - *

                        + *

                        + * The implementation provided here follows the first estimation procedure presented + * here. + *

                        * Preconditions:

                          *
                        • 0 < p < 100 (otherwise an * IllegalArgumentException is thrown)
                        • @@ -313,7 +313,5 @@ final int length, final double p) { return percentile.evaluate(values, begin, length, p); - } - - + } } 1.15 +72 -81 jakarta-commons/math/src/java/org/apache/commons/math/stat/TestStatistic.java Index: TestStatistic.java =================================================================== RCS file: /home/cvs/jakarta-commons/math/src/java/org/apache/commons/math/stat/TestStatistic.java,v retrieving revision 1.14 retrieving revision 1.15 diff -u -r1.14 -r1.15 --- TestStatistic.java 8 Apr 2004 20:46:00 -0000 1.14 +++ TestStatistic.java 11 Apr 2004 19:00:45 -0000 1.15 @@ -25,9 +25,9 @@ public interface TestStatistic { /** - * Computes the Chi-Square statistic comparing - * observed and expected freqeuncy counts. + * Computes the + * Chi-Square statistic comparing observed and expected + * freqeuncy counts. *

                          * This statistic can be used to perform Chi-Square tests. *

                          @@ -53,14 +53,14 @@ /** * 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. - *

                          - * The number returned is the smallest significance level - * at which one can reject the null hypothesis that the observed counts - * conform to the frequency distribution described by the expected counts. + * p-value, associated with a + * + * Chi-square goodness of fit test comparing the observed + * frequency counts to those in the expected array. + *

                          + * The number returned is the smallest significance level at which one can reject + * the null hypothesis that the observed counts conform to the frequency distribution + * described by the expected counts. *

                          * Preconditions:

                            *
                          • Expected counts must all be positive. @@ -83,11 +83,10 @@ throws IllegalArgumentException, MathException; /** - * 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. + * 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. *

                            * Example:
                            * To test the hypothesis that observed follows @@ -118,9 +117,8 @@ throws IllegalArgumentException, MathException; /** - * Computes a t statistic given observed values and - * a comparison constant. + * Computes a + * t statistic given observed values and a comparison constant. *

                            * This statistic can be used to perform a one sample t-test for the mean. *

                            @@ -137,9 +135,8 @@ throws IllegalArgumentException; /** - * Computes a 2-sample t statistic , without the assumption of equal - * sample variances. + * Computes a + * 2-sample t statistic , without the assumption of equal sample variances. *

                            * This statistic can be used to perform a two-sample t-test to compare * sample means. @@ -159,8 +156,8 @@ throws IllegalArgumentException, MathException; /** - * Returns the observed significance level, or + * Returns the observed significance level, or + * * p-value, associated with a two-sample, two-tailed t-test * comparing the means of the input arrays. *

                            @@ -171,13 +168,13 @@ *

                            * The test does not assume that the underlying popuation variances are * equal and it uses approximated degrees of freedom computed from the - * sample data as described here + * sample data as described + * here *

                            * Usage Note:
                            * The validity of the p-value depends on the assumptions of the parametric - * t-test procedure, as discussed here + * t-test procedure, as discussed + * here *

                            * Preconditions:

                              *
                            • The observed array lengths must both be at least 5. @@ -193,11 +190,10 @@ throws IllegalArgumentException, MathException; /** - * Performs a two-sided t-test evaluating the null - * hypothesis that sample1 and sample2 are drawn - * from populations with the same mean, with significance level - * alpha. + * Performs a + * two-sided t-test evaluating the null hypothesis that sample1 + * and sample2 are drawn from populations with the same mean, + * with significance level alpha. *

                              * Returns true iff the null hypothesis that the means are * equal can be rejected with confidence 1 - alpha. To @@ -215,13 +211,13 @@ *

                              * The test does not assume that the underlying popuation variances are * equal and it uses approximated degrees of freedom computed from the - * sample data as described here + * sample data as described + * here *

                              * Usage Note:
                              * The validity of the test depends on the assumptions of the parametric - * t-test procedure, as discussed here + * t-test procedure, as discussed + * here *

                              * Preconditions:

                                *
                              • The observed array lengths must both be at least 5. @@ -241,10 +237,9 @@ throws IllegalArgumentException, MathException; /** - * Performs a two-sided t-test evaluating the null - * hypothesis that the mean of the population from which - * sample is drawn equals mu. + * Performs a + * two-sided t-test evaluating the null hypothesis that the mean of the population from + * which sample is drawn equals mu. *

                                * Returns true iff the null hypothesis can be * rejected with confidence 1 - alpha. To @@ -263,8 +258,7 @@ * Usage Note:
                                * The validity of the test depends on the assumptions of the one-sample * parametric t-test procedure, as discussed - * here + * here *

                                * Preconditions:

                                  *
                                • The observed array length must be at least 5. @@ -281,8 +275,8 @@ throws IllegalArgumentException, MathException; /** - * Returns the observed significance level, or + * Returns the observed significance level, or + * * p-value, associated with a one-sample, two-tailed t-test * comparing the mean of the input array with the constant mu. *

                                  @@ -294,8 +288,8 @@ *

                                  * Usage Note:
                                  * The validity of the test depends on the assumptions of the parametric - * t-test procedure, as discussed here + * t-test procedure, as discussed + * here *

                                  * Preconditions:

                                    *
                                  • The observed array length must be at least 5. @@ -311,9 +305,9 @@ throws IllegalArgumentException, MathException; /** - * Computes a t statistic to use in comparing - * the dataset described by sampleStats to mu. + * Computes a + * t statistic to use in comparing the dataset described by sampleStats + * to mu. *

                                    * This statistic can be used to perform a one sample t-test for the mean. *

                                    @@ -330,9 +324,9 @@ throws IllegalArgumentException; /** - * Computes a 2-sample t statistic , comparing the datasets described - * by two Univariates without the assumption of equal sample variances. + * Computes a + * 2-sample t statistic , comparing the means of the datasets described + * by two {@link StatisticalSummary} instances without the assumption of equal sample variances. *

                                    * This statistic can be used to perform a two-sample t-test to compare * sample means. @@ -342,8 +336,8 @@ * at least 5 observations. *

                                  * - * @param sampleStats1 DescriptiveStatistics describing data from the first sample - * @param sampleStats2 DescriptiveStatistics describing data from the second sample + * @param sampleStats1 StatisticalSummary describing data from the first sample + * @param sampleStats2 StatisticalSummary describing data from the second sample * @return t statistic * @throws IllegalArgumentException if the precondition is not met */ @@ -351,8 +345,8 @@ throws IllegalArgumentException; /** - * Returns the observed significance level, or + * Returns the observed significance level, or + * * p-value, associated with a two-sample, two-tailed t-test * comparing the means of the datasets described by two Univariates. *

                                  @@ -363,13 +357,13 @@ *

                                  * The test does not assume that the underlying popuation variances are * equal and it uses approximated degrees of freedom computed from the - * sample data as described here + * sample data as described + * here *

                                  * Usage Note:
                                  * The validity of the p-value depends on the assumptions of the parametric - * t-test procedure, as discussed here + * t-test procedure, as discussed + * here *

                                  * Preconditions:

                                    *
                                  • The datasets described by the two Univariates must each contain @@ -386,11 +380,10 @@ throws IllegalArgumentException, MathException; /** - * Performs a two-sided t-test evaluating the null - * hypothesis that sampleStats1 and sampleStats2 - * describe datasets drawn from populations with the same mean, with - * significance level alpha. + * Performs a + * two-sided t-test evaluating the null hypothesis that sampleStats1 + * and sampleStats2 describe datasets drawn from populations with the + * same mean, with significance level alpha. *

                                    * Returns true iff the null hypothesis that the means are * equal can be rejected with confidence 1 - alpha. To @@ -409,13 +402,13 @@ *

                                    * The test does not assume that the underlying popuation variances are * equal and it uses approximated degrees of freedom computed from the - * sample data as described here + * sample data as described + * here *

                                    * Usage Note:
                                    * The validity of the test depends on the assumptions of the parametric - * t-test procedure, as discussed here + * t-test procedure, as discussed + * here *

                                    * Preconditions:

                                      *
                                    • The datasets described by the two Univariates must each contain @@ -437,10 +430,9 @@ throws IllegalArgumentException, MathException; /** - * Performs a two-sided t-test evaluating the null - * hypothesis that the mean of the population from which the dataset - * described by stats is drawn equals mu. + * Performs a + * two-sided t-test evaluating the null hypothesis that the mean of the population from + * which the dataset described by stats is drawn equals mu. *

                                      * Returns true iff the null hypothesis can be * rejected with confidence 1 - alpha. To @@ -459,8 +451,7 @@ * Usage Note:
                                      * The validity of the test depends on the assumptions of the one-sample * parametric t-test procedure, as discussed - * here + * here *

                                      * Preconditions:

                                        *
                                      • The sample must include at least 5 observations. @@ -477,8 +468,8 @@ throws IllegalArgumentException, MathException; /** - * Returns the observed significance level, or + * Returns the observed significance level, or + * * p-value, associated with a one-sample, two-tailed t-test * comparing the mean of the dataset described by sampleStats * with the constant mu. @@ -491,8 +482,8 @@ *

                                        * Usage Note:
                                        * The validity of the test depends on the assumptions of the parametric - * t-test procedure, as discussed here + * t-test procedure, as discussed + * here *

                                        * Preconditions:

                                          *
                                        • The sample must contain at least 5 observations. --------------------------------------------------------------------- To unsubscribe, e-mail: commons-dev-unsubscribe@jakarta.apache.org For additional commands, e-mail: commons-dev-help@jakarta.apache.org