People v. Collins, 68 Cal. 2d 319, 66 Cal. Rptr. 497, 438 P.2d 33 (Cal. 1968)
People v. Collins is a landmark California Supreme Court decision that cautions courts and juries against the seductive but often misleading use of statistical probability to prove guilt.
Did the trial court err in admitting and allowing the prosecution to rely on statistical probability testimony, based on unsupported assumptions and independence, to prove the defendants' identity beyond a reasonable doubt?
Expert probability or statistical testimony is inadmissible unless it rests on an adequate evidentiary foundation demonstrating that (1) the underlying frequency data are reliable and derived from the relevant population; (2) the mathematical method used is appropriate to the data; and (3) necessary assumptions—such as independence among variables—are established, not merely asserted. Courts must exclude such evidence when its speculative nature and potential to mislead or unduly prejudice the jury substantially outweigh any probative value. Further, the probability that a randomly selected person (or couple) would match certain traits is not the same as the probability that a particular defendant is guilty given a match; conflating these is error.
Yes. The conviction was reversed because the admission and prosecutorial use of speculative statistical probability evidence, based on unfounded assumptions and an improper independence assumption, constituted prejudicial error.
People v. Collins serves as a canonical warning against "trial by mathematics." It frames core evidentiary safeguards for quantitative or probabilistic proof: empirical grounding, methodological transparency, relevance to the correct population, and avoidance of logical fallacies. The case is regularly cited in modern forensic contexts—DNA, fingerprint statistics, toolmark and bite-mark testimony, and likelihood-ratio presentations—to ensure that numbers presented to juries do not exceed their empirical support or distort the burden of proof. For law students, Collins crystallizes how evidentiary reliability (foundation) and Rule 403-type concerns (prejudice and confusion) converge when courts confront expert statistics.