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Precision is the variation of data around a central value, accuracy is the closeness to the true value. Learn how they differ, often confusing in literature, and implications in statistical analysis.
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Precision versus Accuracy • Precision is the variation of X around <X> • expressed as standard deviation or variance • Accuracy is the closeness of <X> to the “true” value of X • Precision and accuracy are often mixed in the literature
Precision versus Accuracy Precise, not accurate Accurate, not precise Precise and accurate Not accurate and not precise
Precision and true variance Precisionunderestimates true variance Precision equals true variance Precisionoverestimates true variance
Normal distributions and Z-scores X - average Z = -------- sigma Remember this function has two halves. E.g. 68+16+16=100.
Normal distributions andRMS Z-scores X - average Z = --------------- sigma 2 ΣZ RMS-Z = -------- n RMS Z-score~0.5 RMS Z-score=1.0 (reference) RMS Z-score~2
Z-scores and RMS Z-scores • Local geometry RMS Z-scores: • Too tight restraining 0 < RMS Z-score < 1 • Proper Gaussian distribution RMS Z-score 1 • Too loose restraining 1 > RMS Z-score • Structure Z-scores (normally...): • Z-scores > 0 are “better” than average • Z-scores < 0 are “worse” than average • However: AZ-score of -1 is equally likely as a Z-score of +1!! lBoth not good!
