Difference between revisions of "Specificity And Sensitivity"

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Similarly...
 
Similarly...
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* If the truth is positive, PROBABILITY(False Negative) + PROBABILITY(True Positive) = 1.
  
 
* The '''Sensitivity''' is the Probability of a True Positive, assuming the truth is Positive.
 
* The '''Sensitivity''' is the Probability of a True Positive, assuming the truth is Positive.

Revision as of 19:23, 1 August 2016

Specificity and Sensitivity

Medical journals often report the Specificity and Sensitivity of tests for things like HIV or the Zika virus. These measures describe the rates of Type I and Type II errors.

  • Specificity, or sPecificity, concerns the rate of false Positives.
  • Sensitivity or seNsitivity concerns the rate of false Negatives.

This is where it gets confusing...

  • A false positive result means the truth is negative. So the test might have been a true negative instead of being a false positive, those events are disjoint, and if the truth is negative, the result can't be anything else.
  • If the truth is negative, PROBABILITY(False Positive) + PROBABILITY(True Negative) = 1
  • Knowing one probability you can find the other
  • The Specificity is the Probability of a True Negative, assuming the truth is Negative.

Similarly...

  • If the truth is positive, PROBABILITY(False Negative) + PROBABILITY(True Positive) = 1.
  • The Sensitivity is the Probability of a True Positive, assuming the truth is Positive.