assertThat(twoValuesAccumulatorByAddAllStats.mean())
        .isWithin(ALLOWED_ERROR)
        .of(TWO_VALUES_MEAN);
    assertThat(manyValuesAccumulatorByAddAllIterable.mean())
        .isWithin(ALLOWED_ERROR)
        .of(MANY_VALUES_MEAN);
    assertThat(manyValuesAccumulatorByAddAllIterator.mean())
        .isWithin(ALLOWED_ERROR)
        .of(MANY_VALUES_MEAN);

   */
  @Deprecated
  public static double mean(long... values) {
    checkArgument(values.length > 0, "Cannot take mean of 0 values");
    long count = 1;
    double mean = values[0];
    for (int index = 1; index < values.length; ++index) {
      count++;
      // Art of Computer Programming vol. 2, Knuth, 4.2.2, (15)
      mean += (values[index] - mean) / count;
    }
    return mean;
  }

  /**

      DoubleMath.mean(Double.POSITIVE_INFINITY);
      fail("Expected IllegalArgumentException");
    } catch (IllegalArgumentException expected) {
    }
  }

  @GwtIncompatible // DoubleMath.mean
  public void testMean_intVarargs() {
    assertEquals(-13.75, DoubleMath.mean(11, -22, 44, -88), 1.0e-10);
    assertEquals(11.0, DoubleMath.mean(11), 1.0e-10);
  }

  @GwtIncompatible // DoubleMath.mean

      }
    } else {
      count++;
      if (isFinite(value) && isFinite(mean)) {
        // Art of Computer Programming vol. 2, Knuth, 4.2.2, (15) and (16)
        double delta = value - mean;
        mean += delta / count;
        sumOfSquaresOfDeltas += delta * (value - mean);
      } else {
        mean = calculateNewMeanNonFinite(mean, value);
        sumOfSquaresOfDeltas = NaN;
      }
      min = Math.min(min, value);

      DoubleMath.mean(Double.POSITIVE_INFINITY);
      fail("Expected IllegalArgumentException");
    } catch (IllegalArgumentException expected) {
    }
  }

  @GwtIncompatible // DoubleMath.mean
  public void testMean_intVarargs() {
    assertEquals(-13.75, DoubleMath.mean(11, -22, 44, -88), 1.0e-10);
    assertEquals(11.0, DoubleMath.mean(11), 1.0e-10);
  }

  @GwtIncompatible // DoubleMath.mean

      // in NaN naturally.
      sumOfProductsOfDeltas +=
          values.sumOfProductsOfDeltas()
              + (values.xStats().mean() - xStats.mean())
                  * (values.yStats().mean() - yStats.mean())
                  * values.count();
    }
    yStats.addAll(values.yStats());
  }

  /** Returns an immutable snapshot of the current statistics. */

http://www.apache.org/licenses/ 

1. Definitions.

"License" shall mean the terms and conditions for use, reproduction, and 
distribution as defined by Sections 1 through 9 of this document. 

"Licensor" shall mean the copyright owner or entity authorized by the 
copyright owner that is granting the License. 

"Legal Entity" shall mean the union of the acting entity and all other 

      }
    }
    assertThat(MANY_VALUES_STATS_ITERABLE.mean()).isWithin(ALLOWED_ERROR).of(MANY_VALUES_MEAN);
    assertThat(MANY_VALUES_STATS_ITERATOR.mean()).isWithin(ALLOWED_ERROR).of(MANY_VALUES_MEAN);
    assertThat(MANY_VALUES_STATS_SNAPSHOT.mean()).isWithin(ALLOWED_ERROR).of(MANY_VALUES_MEAN);
    assertThat(LARGE_VALUES_STATS.mean())
        .isWithin(ALLOWED_ERROR * Double.MAX_VALUE)
        .of(LARGE_VALUES_MEAN);

      if (isFinite(value) && isFinite(mean)) {
        // Art of Computer Programming vol. 2, Knuth, 4.2.2, (15)
        mean += (value - mean) / (index + 1);
      } else {
        mean = calculateNewMeanNonFinite(mean, value);
      }
    }
    return mean;
  }

  /**
   * Returns the <a href="http://en.wikipedia.org/wiki/Arithmetic_mean">arithmetic mean</a> of the
   * values. The count must be non-zero.

        twoValuesAccumulator.xStats().mean(),
        twoValuesAccumulator.yStats().mean(),
        twoValuesAccumulator.xStats().populationVariance(),
        twoValuesAccumulator.populationCovariance());
    assertDiagonalLinearTransformation(
        twoValuesAccumulatorByAddAllPartitionedPairedStats.leastSquaresFit(),
        twoValuesAccumulatorByAddAllPartitionedPairedStats.xStats().mean(),