HL7 Terminology
1.0.0 - Publication

This page is part of the HL7 Terminology (v1.0.0: Release) based on FHIR R4. The current version which supercedes this version is 5.2.0. For a full list of available versions, see the Directory of published versions

## StatisticsCode

Summary

 Defining URL: http://terminology.hl7.org/ValueSet/observation-statistics Version: 4.1.0 Name: StatisticsCode Status: draft Title: StatisticsCode Definition: The statistical operation parameter -"statistic" codes. Publisher: HL7 (FHIR Project) Committee: Orders and Observations OID: 2.16.840.1.113883.4.642.3.405 (for OID based terminology systems) Source Resource: XML / JSON / Turtle

References

This value set is not used

### Expansion

This value set contains 21 concepts

Expansion based on StatisticsCode v4.2.0 (CodeSystem)

All codes from system `http://terminology.hl7.org/CodeSystem/observation-statistics`

 Code Display Definition average Average The [mean](https://en.wikipedia.org/wiki/Arithmetic_mean) of N measurements over the stated period. maximum Maximum The [maximum](https://en.wikipedia.org/wiki/Maximal_element) value of N measurements over the stated period. minimum Minimum The [minimum](https://en.wikipedia.org/wiki/Minimal_element) value of N measurements over the stated period. count Count The [number] of valid measurements over the stated period that contributed to the other statistical outputs. total-count Total Count The total [number] of valid measurements over the stated period, including observations that were ignored because they did not contain valid result values. median Median The [median](https://en.wikipedia.org/wiki/Median) of N measurements over the stated period. std-dev Standard Deviation The [standard deviation](https://en.wikipedia.org/wiki/Standard_deviation) of N measurements over the stated period. sum Sum The [sum](https://en.wikipedia.org/wiki/Summation) of N measurements over the stated period. variance Variance The [variance](https://en.wikipedia.org/wiki/Variance) of N measurements over the stated period. 20-percent 20th Percentile The 20th [Percentile](https://en.wikipedia.org/wiki/Percentile) of N measurements over the stated period. 80-percent 80th Percentile The 80th [Percentile](https://en.wikipedia.org/wiki/Percentile) of N measurements over the stated period. 4-lower Lower Quartile The lower [Quartile](https://en.wikipedia.org/wiki/Quartile) Boundary of N measurements over the stated period. 4-upper Upper Quartile The upper [Quartile](https://en.wikipedia.org/wiki/Quartile) Boundary of N measurements over the stated period. 4-dev Quartile Deviation 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. 5-1 1st Quintile 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. 5-2 2nd Quintile The second of four values that divide the N measurements into a frequency distribution of five classes with each containing one fifth of the total population. 5-3 3rd Quintile The third of four values that divide the N measurements into a frequency distribution of five classes with each containing one fifth of the total population. 5-4 4th Quintile The fourth of four values that divide the N measurements into a frequency distribution of five classes with each containing one fifth of the total population. skew Skew Skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean. The skewness value can be positive or negative, or even undefined. Source: [Wikipedia](https://en.wikipedia.org/wiki/Skewness). kurtosis Kurtosis 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). regression Regression 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.