How to use

getN

method

in

org.apache.commons.math.stat.descriptive.StatisticalSummary

/** Check sample data.
 * @param stat statistical summary
 * @exception IllegalArgumentException if there is not enough sample data
 */
private void checkSampleData(final StatisticalSummary stat)
  throws IllegalArgumentException {
  if ((stat == null) || (stat.getN() < 2)) {
    throw MathRuntimeException.createIllegalArgumentException(
       INSUFFICIENT_DATA_MESSAGE,
       (stat == null) ? 0 : stat.getN());
  }
}

/** Check sample data.
 * @param stat statistical summary
 * @exception IllegalArgumentException if there is not enough sample data
 */
private void checkSampleData(final StatisticalSummary stat)
  throws IllegalArgumentException {
  if ((stat == null) || (stat.getN() < 2)) {
    throw MathRuntimeException.createIllegalArgumentException(
       LocalizedFormats.INSUFFICIENT_DATA_FOR_T_STATISTIC,
       (stat == null) ? 0 : stat.getN());
  }
}

/**
 * Computes a <a href="http://www.itl.nist.gov/div898/handbook/prc/section2/prc22.htm#formula">
 * t statistic </a> to use in comparing the mean of the dataset described by 
 * <code>sampleStats</code> to <code>mu</code>.
 * <p>
 * This statistic can be used to perform a one sample t-test for the mean.
 * </p><p>
 * <strong>Preconditions</strong>: <ul>
 * <li><code>observed.getN() > = 2</code>.
 * </li></ul></p>
 *
 * @param mu comparison constant
 * @param sampleStats DescriptiveStatistics holding sample summary statitstics
 * @return t statistic
 * @throws IllegalArgumentException if the precondition is not met
 */
public double t(double mu, StatisticalSummary sampleStats)
throws IllegalArgumentException {
  if ((sampleStats == null) || (sampleStats.getN() < 2)) {
    throw new IllegalArgumentException("insufficient data for t statistic");
  }
  return t(sampleStats.getMean(), mu, sampleStats.getVariance(),
      sampleStats.getN());
}

throws IllegalArgumentException, MathException {
  if ((sampleStats1 == null) || (sampleStats2 == null ||
      Math.min(sampleStats1.getN(), sampleStats2.getN()) < 2)) {
    throw new IllegalArgumentException("insufficient data for t statistic");
      sampleStats2.getVariance(), (double) sampleStats1.getN(), 
      (double) sampleStats2.getN());

throws IllegalArgumentException, MathException {
  if ((sampleStats1 == null) || (sampleStats2 == null ||
      Math.min(sampleStats1.getN(), sampleStats2.getN()) < 2)) {
    throw new IllegalArgumentException("insufficient data for t statistic");
      sampleStats2.getVariance(), (double) sampleStats1.getN(), 
      (double) sampleStats2.getN());

if ((sampleStats == null) || (sampleStats.getN() < 2)) {
  throw new IllegalArgumentException("insufficient data for t statistic");
    sampleStats.getN());

if ((sampleStats1 == null) ||
    (sampleStats2 == null ||
        Math.min(sampleStats1.getN(), sampleStats2.getN()) < 2)) {
  throw new IllegalArgumentException("insufficient data for t statistic");
    (double) sampleStats1.getN(), (double) sampleStats2.getN());

if ((sampleStats1 == null) ||
    (sampleStats2 == null ||
        Math.min(sampleStats1.getN(), sampleStats2.getN()) < 2)) {
  throw new IllegalArgumentException("insufficient data for t statistic");
    (double) sampleStats1.getN(), (double) sampleStats2.getN());

/**
 * Computes a <a href="http://www.itl.nist.gov/div898/handbook/prc/section2/prc22.htm#formula">
 * t statistic </a> to use in comparing the mean of the dataset described by
 * <code>sampleStats</code> to <code>mu</code>.
 * <p>
 * This statistic can be used to perform a one sample t-test for the mean.
 * </p><p>
 * <strong>Preconditions</strong>: <ul>
 * <li><code>observed.getN() > = 2</code>.
 * </li></ul></p>
 *
 * @param mu comparison constant
 * @param sampleStats DescriptiveStatistics holding sample summary statitstics
 * @return t statistic
 * @throws IllegalArgumentException if the precondition is not met
 */
public double t(double mu, StatisticalSummary sampleStats)
throws IllegalArgumentException {
  checkSampleData(sampleStats);
  return t(sampleStats.getMean(), mu, sampleStats.getVariance(),
      sampleStats.getN());
}

checkSampleData(sampleStats2);
return tTest(sampleStats1.getMean(), sampleStats2.getMean(), sampleStats1.getVariance(),
    sampleStats2.getVariance(), sampleStats1.getN(),
    sampleStats2.getN());

return homoscedasticTTest(sampleStats1.getMean(),
    sampleStats2.getMean(), sampleStats1.getVariance(),
    sampleStats2.getVariance(), sampleStats1.getN(),
    sampleStats2.getN());

/**
 * Computes a <a href="http://www.itl.nist.gov/div898/handbook/prc/section2/prc22.htm#formula">
 * t statistic </a> to use in comparing the mean of the dataset described by
 * <code>sampleStats</code> to <code>mu</code>.
 * <p>
 * This statistic can be used to perform a one sample t-test for the mean.
 * </p><p>
 * <strong>Preconditions</strong>: <ul>
 * <li><code>observed.getN() > = 2</code>.
 * </li></ul></p>
 *
 * @param mu comparison constant
 * @param sampleStats DescriptiveStatistics holding sample summary statitstics
 * @return t statistic
 * @throws IllegalArgumentException if the precondition is not met
 */
public double t(double mu, StatisticalSummary sampleStats)
throws IllegalArgumentException {
  checkSampleData(sampleStats);
  return t(sampleStats.getMean(), mu, sampleStats.getVariance(),
      sampleStats.getN());
}

return homoscedasticT(sampleStats1.getMean(), sampleStats2.getMean(),
    sampleStats1.getVariance(), sampleStats2.getVariance(),
    sampleStats1.getN(), sampleStats2.getN());

return t(sampleStats1.getMean(), sampleStats2.getMean(),
    sampleStats1.getVariance(), sampleStats2.getVariance(),
    sampleStats1.getN(), sampleStats2.getN());

return homoscedasticTTest(sampleStats1.getMean(),
    sampleStats2.getMean(), sampleStats1.getVariance(),
    sampleStats2.getVariance(), sampleStats1.getN(),
    sampleStats2.getN());

return homoscedasticT(sampleStats1.getMean(), sampleStats2.getMean(),
    sampleStats1.getVariance(), sampleStats2.getVariance(),
    sampleStats1.getN(), sampleStats2.getN());

return t(sampleStats1.getMean(), sampleStats2.getMean(),
    sampleStats1.getVariance(), sampleStats2.getVariance(),
    sampleStats1.getN(), sampleStats2.getN());

checkSampleData(sampleStats2);
return tTest(sampleStats1.getMean(), sampleStats2.getMean(), sampleStats1.getVariance(),
    sampleStats2.getVariance(), sampleStats1.getN(),
    sampleStats2.getN());

checkSampleData(sampleStats);
return tTest(sampleStats.getMean(), mu, sampleStats.getVariance(),
    sampleStats.getN());

checkSampleData(sampleStats);
return tTest(sampleStats.getMean(), mu, sampleStats.getVariance(),
    sampleStats.getN());