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1.  final def !=(arg0: Any): Boolean

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2.  final def ##(): Int

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3.  def +(b: SampleStats[A])(implicit E: Equal[A], F: Field[A]): SampleStats[A]

   Alias for merge.

4.  final def ==(arg0: Any): Boolean

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5.  final def asInstanceOf[T0]: T0

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6.  def clone(): AnyRef

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7.  final def eq(arg0: AnyRef): Boolean

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8.  def excessKurtosis(implicit E: Equal[A], F: Field[A]): slamdata.Predef.Option[A]
9.  def finalize(): Unit

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10.  final def getClass(): Class[_]

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11.  final def isInstanceOf[T0]: Boolean

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12.  def kurtosis(implicit E: Equal[A], F: Field[A]): slamdata.Predef.Option[A]
13.  val m1: A
14.  val m2: A
15.  val m3: A
16.  val m4: A
17.  def mean: A
18.  def merge(b: SampleStats[A])(implicit E: Equal[A], F: Field[A]): SampleStats[A]

    Combine with another SampleStats to produce stats about the union of their observations.

    Combine with another SampleStats to produce stats about the union of their observations.

    Implementation via Chan et al. https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Parallel_algorithm

19.  final def ne(arg0: AnyRef): Boolean

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20.  final def notify(): Unit

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21.  final def notifyAll(): Unit

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22.  def observe(x: A)(implicit F: Field[A]): SampleStats[A]

    Returns new stats that include the given observation.

    Returns new stats that include the given observation.

    NB: This is equivalent to merge, simplified for the case when one of the stats has exactly one observation.

23.  def populationExcessKurtosis(implicit E: Equal[A], F: Field[A]): slamdata.Predef.Option[A]

    Estimated excess kurtosis of the population sampled.

24.  def populationKurtosis(implicit E: Equal[A], F: Field[A]): slamdata.Predef.Option[A]

    Estimated kurtosis of the population sampled.

25.  def populationSkewness(implicit E: Equal[A], F: Field[A], R: NRoot[A]): slamdata.Predef.Option[A]

    Estimated skewness of the population sampled.

26.  def populationStddev(implicit E: Equal[A], F: Field[A], R: NRoot[A]): slamdata.Predef.Option[A]

    Estimated standard deviation of the population sampled.

27.  def populationVariance(implicit E: Equal[A], F: Field[A]): slamdata.Predef.Option[A]

    Unbiased estimated variance of the population sampled.

28.  val size: A
29.  def skewness(implicit E: Equal[A], F: Field[A], R: NRoot[A]): slamdata.Predef.Option[A]
30.  def stddev(implicit E: Equal[A], F: Field[A], R: NRoot[A]): slamdata.Predef.Option[A]
31.  final def synchronized[T0](arg0: ⇒ T0): T0

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32.  def variance(implicit E: Equal[A], F: Field[A]): slamdata.Predef.Option[A]
33.  final def wait(): Unit

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34.  final def wait(arg0: Long, arg1: Int): Unit

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35.  final def wait(arg0: Long): Unit

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