False positive rate

In statistics, when performing multiple comparisons, a false positive ratio (also known as fall-out or false alarm rate[1] ) is the probability of falsely rejecting the null hypothesis for a particular test. The false positive rate is calculated as the ratio between the number of negative events wrongly categorized as positive (false positives) and the total number of actual negative events (regardless of classification).

The false positive rate (or "false alarm rate") usually refers to the expectancy of the false positive ratio.

  1. ^ "Forecast Verification methods Across Time and Space Scales". WWRP/WGNE Joint Working Group on Forecast Verification Research. Archived from the original on 27 December 2024. Retrieved 8 January 2025.

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