:py:mod:`spark_auto_mapper_fhir.value_sets.statistics_code`
===========================================================

.. py:module:: spark_auto_mapper_fhir.value_sets.statistics_code


Module Contents
---------------

Classes
~~~~~~~

.. autoapisummary::

   spark_auto_mapper_fhir.value_sets.statistics_code.StatisticsCodeCode
   spark_auto_mapper_fhir.value_sets.statistics_code.StatisticsCodeCodeValues




.. py:class:: StatisticsCodeCode(value)

   Bases: :py:obj:`spark_auto_mapper_fhir.value_sets.generic_type.GenericTypeCode`

   StatisticsCode
   From: http://terminology.hl7.org/CodeSystem/observation-statistics in valuesets.xml
       The statistical operation parameter -"statistic" codes.

   .. py:attribute:: codeset
      :annotation: :spark_auto_mapper_fhir.fhir_types.uri.FhirUri = http://terminology.hl7.org/CodeSystem/observation-statistics

      


.. py:class:: StatisticsCodeCodeValues

   The [mean](https://en.wikipedia.org/wiki/Arithmetic_mean) of N measurements
   over the stated period.
   From: http://terminology.hl7.org/CodeSystem/observation-statistics in valuesets.xml

   .. py:attribute:: Average
      

      The [maximum](https://en.wikipedia.org/wiki/Maximal_element) value of N
      measurements over the stated period.
      From: http://terminology.hl7.org/CodeSystem/observation-statistics in valuesets.xml


   .. py:attribute:: Maximum
      

      The [minimum](https://en.wikipedia.org/wiki/Minimal_element) value of N
      measurements over the stated period.
      From: http://terminology.hl7.org/CodeSystem/observation-statistics in valuesets.xml


   .. py:attribute:: Minimum
      

      The [number] of valid measurements over the stated period that contributed to
      the other statistical outputs.
      From: http://terminology.hl7.org/CodeSystem/observation-statistics in valuesets.xml


   .. py:attribute:: Count
      

      The total [number] of valid measurements over the stated period, including
      observations that were ignored because they did not contain valid result
      values.
      From: http://terminology.hl7.org/CodeSystem/observation-statistics in valuesets.xml


   .. py:attribute:: TotalCount
      

      The [median](https://en.wikipedia.org/wiki/Median) of N measurements over the
      stated period.
      From: http://terminology.hl7.org/CodeSystem/observation-statistics in valuesets.xml


   .. py:attribute:: Median
      

      The [standard deviation](https://en.wikipedia.org/wiki/Standard_deviation) of
      N measurements over the stated period.
      From: http://terminology.hl7.org/CodeSystem/observation-statistics in valuesets.xml


   .. py:attribute:: StandardDeviation
      

      The [sum](https://en.wikipedia.org/wiki/Summation) of N measurements over the
      stated period.
      From: http://terminology.hl7.org/CodeSystem/observation-statistics in valuesets.xml


   .. py:attribute:: Sum
      

      The [variance](https://en.wikipedia.org/wiki/Variance) of N measurements over
      the stated period.
      From: http://terminology.hl7.org/CodeSystem/observation-statistics in valuesets.xml


   .. py:attribute:: Variance
      

      The 20th [Percentile](https://en.wikipedia.org/wiki/Percentile) of N
      measurements over the stated period.
      From: http://terminology.hl7.org/CodeSystem/observation-statistics in valuesets.xml


   .. py:attribute:: LowerQuartile
      

      The upper [Quartile](https://en.wikipedia.org/wiki/Quartile) Boundary of N
      measurements over the stated period.
      From: http://terminology.hl7.org/CodeSystem/observation-statistics in valuesets.xml


   .. py:attribute:: UpperQuartile
      

      The difference between the upper and lower
      [Quartiles](https://en.wikipedia.org/wiki/Quartile) is called the
      Interquartile range. (IQR = Q3-Q1) Quartile deviation or Semi-interquartile
      range is one-half the difference between the first and the third quartiles.
      From: http://terminology.hl7.org/CodeSystem/observation-statistics in valuesets.xml


   .. py:attribute:: QuartileDeviation
      

      The lowest of four values that divide the N measurements into a frequency
      distribution of five classes with each containing one fifth of the total
      population.
      From: http://terminology.hl7.org/CodeSystem/observation-statistics in valuesets.xml


   .. py:attribute:: Skew
      

      Kurtosis  is a measure of the "tailedness" of the probability distribution of
      a real-valued random variable.   Source:
      [Wikipedia](https://en.wikipedia.org/wiki/Kurtosis).
      From: http://terminology.hl7.org/CodeSystem/observation-statistics in valuesets.xml


   .. py:attribute:: Kurtosis
      

      Linear regression is an approach for modeling two-dimensional sample points
      with one independent variable and one dependent variable (conventionally, the
      x and y coordinates in a Cartesian coordinate system) and finds a linear
      function (a non-vertical straight line) that, as accurately as possible,
      predicts the dependent variable values as a function of the independent
      variables. Source:
      [Wikipedia](https://en.wikipedia.org/wiki/Simple_linear_regression)  This
      Statistic code will return both a gradient and an intercept value.
      From: http://terminology.hl7.org/CodeSystem/observation-statistics in valuesets.xml


   .. py:attribute:: Regression