{
  "package" : "hl7.fhir.r5.core@5.0.0",
  "definition" : "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.",
  "system" : "http://hl7.org/fhir/observation-statistics",
  "property" : [ ],
  "codesystem" : "23ab4636-6531-57a2-9b71-0ec21b4570c8",
  "concept_id" : "0ce330ec-388a-5142-8e59-d5373de2db1f",
  "ancestors" : {
    "regression" : 0
  },
  "id" : "838c43b7-ccda-428d-9f21-af27fc12cba0",
  "code" : "regression",
  "display" : "Regression",
  "version" : "5.0.0"
}