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stats

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object stats

Miscellaneous statistics-related functions.

Note: You must import scala.math.Numeric (or just Numeric._) for these functions to work. For example:

import Numeric._
import grizzled.math.stats._

val l = List[Double]( ... )
println(median(l))

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final def ##(): Int

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def arithmeticMean[T](items: T*)(implicit n: Numeric[T]): Double

Calculates the arithmetic mean of the values of the passed-in numbers.
Calculates the arithmetic mean of the values of the passed-in numbers.
items
the numbers on which to operate
returns
the arithmetic mean
final def asInstanceOf[T0]: T0

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def clone(): AnyRef

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def geometricMean[T](items: T*)(implicit n: Numeric[T]): Double

Calculates the geometric mean of the values of the passed-in numbers, namely, the n-th root of (x1 * x2 * ...
Calculates the geometric mean of the values of the passed-in numbers, namely, the n-th root of (x1 * x2 * ... * xn). Note that all numbers used in the calculation of a geometric mean must be positive.
For a discussion of when a geometric mean is more suitable than an arithmetic mean, see http://www.math.toronto.edu/mathnet/questionCorner/geomean.html.
items
the numbers on which to operate
returns
the geometric mean
final def getClass(): Class[_]

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def harmonicMean[T](items: T*)(implicit n: Numeric[T]): Double

Calculates the harmonic mean of the values of the passed-in numbers, namely: n / (1/x¹ + 1/x² + ... + 1/xⁿ).
Calculates the harmonic mean of the values of the passed-in numbers, namely: n / (1/x¹ + 1/x² + ... + 1/xⁿ).
items
the numbers on which to operate
returns
the harmonic mean
def hashCode(): Int

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final def isInstanceOf[T0]: Boolean

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def mean[T](items: T*)(implicit n: Numeric[T]): Double

Synonym for arithmeticMean.
Synonym for arithmeticMean.

See also
arithmeticMean
def median[T](items: T*)(implicit n: Numeric[T]): Double

Calculates the median of the values of the passed-in numbers.
Calculates the median of the values of the passed-in numbers.
items
the numbers on which to operate
returns
the median
def mode[T](items: T*)(implicit n: Numeric[T]): List[T]

Calculates the mode (most common value(s)) of the values of the passed-in numbers.
Calculates the mode (most common value(s)) of the values of the passed-in numbers. If there are multiple common values, they're all returned.
items
the numbers on which to operate
returns
list of modal values
final def ne(arg0: AnyRef): Boolean

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def popStdDev[T](items: T*)(implicit n: Numeric[T]): Double

Shorter synonym for populationStandardDeviation.
Shorter synonym for populationStandardDeviation.

See also
populationStandardDeviation
def populationStandardDeviation[T](items: T*)(implicit n: Numeric[T]): Double

Calculate the population standard deviation of the specified values.
Calculate the population standard deviation of the specified values. The population standard deviation is merely the square root of the population variance. Thus, this function is just shorthand for:
```
java.lang.Math.sqrt(populationVariance(items))
```
items
the numbers on which to operate
returns
the standard deviation
def populationVariance[T](items: T*)(implicit n: Numeric[T]): Double

Calculate the population variance of the finite population defined by the items arguments.
Calculate the population variance of the finite population defined by the items arguments. The population variance is defined as:
```
1
- *  SUM(i=1, N) { (x[i] - mean)^2^ }
N
```
See:
- http://en.wikipedia.org/wiki/Variance#Population_variance_and_sample_variance - http://www.quickmba.com/stats/standard-deviation/
items
the numbers on which to operate
returns
the variance
def range[T](items: T*)(implicit n: Numeric[T]): T

Calculate the range of a data set.
Calculate the range of a data set. This function does a single linear pass over the data set.
items
the numbers on which to operate
returns
the range
def sampleStandardDeviation[T](items: T*)(implicit n: Numeric[T]): Double

Calculate the sample standard deviation of the specified values.
Calculate the sample standard deviation of the specified values. The sample standard deviation is merely the square root of the sample variance. Thus, this function is just shorthand for:
```
java.lang.Math.sqrt(sampleVariance(items))
```
items
the numbers on which to operate
returns
the standard deviation
def sampleStdDev[T](items: T*)(implicit n: Numeric[T]): Double

Shorter synonym for sampleStandardDeviation.
Shorter synonym for sampleStandardDeviation.

See also
populationStandardDeviation
def sampleVariance[T](items: T*)(implicit n: Numeric[T]): Double

Calculate the unbiased sample variance of the finite sample defined by the items arguments.
Calculate the unbiased sample variance of the finite sample defined by the items arguments. The sample variance is defined as:
```
  1
----- *   SUM(i=1, N) { (x[i] - sampleMean)^2^  }
N - 1
```
See:
- http://en.wikipedia.org/wiki/Variance#Population_variance_and_sample_variance - http://www.quickmba.com/stats/standard-deviation/
items
the numbers on which to operate
returns
the variance
final def synchronized[T0](arg0: ⇒ T0): T0

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