{
  "package" : "hl7.terminology.r4@6.3.0",
  "definition" : "The strength of correlation between a set (2 or more) of random variables. The covariance is obtained by forming: cov(x,y)=e([x-e(x)][y-e(y)] where e(x), e(y) is the expected value (mean) of variable x and y respectively. Covariance is symmetric so cov(x,y)=cov(y,x). The covariance is usefull when looking at the variance of the sum of the 2 random variables since: var(x+y) = var(x) +var(y) +2cov(x,y) the covariance cov(x,y) is used to obtain the coefficient of correlation cor(x,y) by normalizing (dividing) cov(x,y) but the product of the standard deviations of x and y.",
  "system" : "http://terminology.hl7.org/CodeSystem/statistic-type",
  "property" : [ ],
  "codesystem" : "fca7c533-16e4-5047-a0b4-a8f0d355a8a0",
  "concept_id" : "6ac96940-4099-5bf5-b4a0-6f9cf7e5b250",
  "ancestors" : {
    "0000301" : 0
  },
  "id" : "521faa9e-f699-42dc-a7f1-dca1fd1b516a",
  "code" : "0000301",
  "display" : "Covariance",
  "version" : "1.0.1"
}