No apologies: I have not attempted to research this (beyond reviewing the list of questions CV provided that may have answered this query). I taught this in class last week for diagnosing logistic multiple regression models, and I warned the students in advance that I did not know the origins of the name.

What is the history of the name of the ROC curve: Receiver Operating Characteristic?

I recall something about it being mentioned in an avocational book (like The Lady Tasting Tea or one of Mario Livio's books)...but if anyone has some history to share, that would be welcome.

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    $\begingroup$ There's a section in Wikipedia with links to citations and all right here. The "receiver" was picking up enemy radars and trying to intercept communication. Operating characteristics is literally "how well it works". $\endgroup$
    – AdamO
    Apr 17, 2018 at 13:40
  • $\begingroup$ Very useful link...now I wonder what the references are that first connect the signal detection field to medical literature. $\endgroup$
    – Gregg H
    Apr 17, 2018 at 13:51
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    $\begingroup$ you can read link 34 $\endgroup$
    – AdamO
    Apr 17, 2018 at 13:52
  • $\begingroup$ Very helpful answers, but why was this metric given such a clunky name? The point I think must have been to define its limitations. Because the ROC is not what Churchill would have been interested in. He would have wanted something that measured the effectiveness of the entire radar air defence system in knocking out enemy bombers, not which told him about the effectiveness of an operator of one component. $\endgroup$ Jan 1 at 10:11

3 Answers 3


The earliest book reference that I know of is

Woodward, P. M. (1953). Probability and information theory with applications to radar. London: Pergamon Press.

but the concept, which was developed during World War II for the analysis of radar receivers, might have been published earlier than 1953 in journal articles (after the War was over) or in the multivolume series of texts published by the MIT Radiation Laboratory about their research during World War II.

  • $\begingroup$ @Nick-Cox / dilip-sarwate : I found the book online but couldn't find which page contains the ROC terminology. Can you advise? - Thanks. $\endgroup$ Dec 14, 2019 at 3:25

Earliest article I can find is from 1954:

  • Peterson, W., Birdsall, T., Fox, W. (1954). The theory of signal detectability, Transactions of the IRE Professional Group on Information Theory, 4, 4, pp. 171 - 212.


An optimum observer required to give a yes or no answer simply chooses an operating level and concludes that the receiver input arose from signal plus noise only when this level is exceeded by the output of his likelihood ratio receiver. Associated with each such operating level are conditional probabilities that the answer is a false alarm and the conditional probability of detection. Graphs of these quantities called receiver operating characteristic, or ROC, curves are convenient for evaluating a receiver. If the detection problem is changed by varying, for example, the signal power, then a family of ROC curves is generated. Such things as betting curves can easily be obtained from such a family.

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    $\begingroup$ Note that this is after the book listed in the existing answer. It could be the first article, though. $\endgroup$ Mar 18, 2019 at 15:28

Carleton Douglas Creelman writes in History of Signal Detection Theory

Subsequent to the end of WWII, and the end of tight security around theoretical work in the field, academically connected laboratories, such as those at MIT and the University of Michigan, published work describing ways to analyze faint, noise-contaminated signals. From the Research Laboratory of Electronics at MIT, van Meter and Middleton (1954) published their analysis of the problem of extracting a signal that is imbedded in noise. Davenport and Root (1958) provided a comprehensive text on the engineering issues surrounding signal extraction. At the University of Michigan, Peterson et al. (1954) addressed the same issues, arriving at some of the same theoretical findings, and built on them by adding consideration of the decision processes required. The technique involved two core ideas: detection should involve correlation of a known signal with the noise-masked input and the input signal could be fully characterized by sampling at a rate determined by the bandwidth of the noise and the duration of the observation.


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