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Techniques used in forensic analysis have to find an appropriate balance between fairness to the defendant and efficiency and safety for forensic personnel. Safety issues are particularly acute in analyzing large seizures of bags likely containing heroin, possibly laced with fentanyl. National and local law specifies penalties that depend on the weight of seized powder containing heroin. Local custom makes available to the prosecution and the defense a preliminary report showing the presence of heroin and an indication of the powder weight seized. Such a report, even if it involves uncertainty, can be useful to both parties in understanding the likely sentencing range, with a view toward plea bargaining. An earlier methodological paper demonstrates how data from a sample of bags can be used to create a probability distribution for the weight of seized powder. The aim of this paper is to study whether sampling itself creates substantial additional uncertainty. To this end, we apply the above method to four populations with weights known for each item in the population. We draw eight random samples of size five from each population. Applying the proposed method to each sample, the results show that the variation created by drawing these samples is trivial. We conclude that the proposed method, which is convenient and safer for personnel, can be used without prejudice against the defendant.

For Bayesian inference to be useful to a court, it is essential that the priors used should be neutral between the parties. ‘Neutrality’ reflects the idea that the fact-finder would want the statistical analyses to be fair to both parties. It is neither the same as the legal designation of which party has the burden of proof with respect to a particular matter, nor the standard of proof that must be met for that party to prevail. The recent case of Idaho v. Ish raises the question of how to find such priors, particularly in a doubly constrained 2 × 2 table with a zero. This article re-examines this issue. It also offers reflection on whether, given a zero in the table (which here means that all members of a particular race or sex are excluded from jury service), it matters how many are excluded.

This is a story of a lawsuit in Japan, about an alleged incident in America thirty years before. The focus of the analysis is comparing the rates of skips in ballpoint pen writing in a diary. Chernoff proposed several methods to address the comparison between the skips observed in different passages in the diary. I also give my own alternative analysis of the data.

We propose a method that yields a probability distribution for the net weight of drug powder resulting from a seizure of stamp bags. The technique involves the posterior predictive distribution of a beta distribution under a conjugate prior. The convolution of two distributions is computed for two visually distinct groups of stamp bags from the same seizure.

A familiar defense of Personalist or Subjective Bayesian theory is that, under a variety of sufficient conditions, asymptotically—with increasing shared evidence—almost surely, each non-extreme, countably additive Bayesian opinion, when updated by conditionalization, converges to certainty that is veridical about the truth/falsity of hypotheses of interest. Then, with probability 1 over possible evidential histories, personal probabilities track the truth. In this note we examine varieties of failures of these asymptotics. In an extreme case, conditional probabilities are deceptive when they converge to certainty for a false hypothesis. We establish that proposals for so-called “modest” credences, offered by Elga (2016) and by Nielsen and Stewart (2019) in response to a concern about Bayesian orgulity raised by Belot (2013), instead support deceptive credences. We argue that deceptive credences are not modest, but for a reason different than Belot adduces.

Civil liability for a lost chance occurs when a tortious action changes the probabilities of the outcomes that can be obtained by the victim. In such situations, the most commonly referenced rule of quantification is that of proportional damages. Based on this rule, the literature has proposed several formulae for quantifying damages. However, these formulae have limited applicability. For instance, they are inappropriate when the victim’s chance has more than two possible outcomes or when the victim can make a choice which would influence her outcomes. Also, the formulae have seldom been derived from legal principles, which makes it hard to choose among them when they disagree. Instead of discussing specific formulae, we propose a principled approach to quantifying damages in lost chances. We present several qualitative legal questions regarding how to quantify damages and show that the answers lead to precise and general rules for damage quantification. These rules generalize the formulae that were previously proposed. Furthermore, our approach separates legal considerations from the quantitative issues involved in damage quantification.

Everyone knows that fingerprint evidence can be extremely incriminating. What is less clear is whether the way that a fingerprint examiner describes that evidence influences the weight lay jurors assign to it. This essay describes an experiment testing how lay people respond to different presentations of fingerprint evidence in a hypothetical criminal case. We find that people attach more weight to the evidence when the fingerprint examiner indicates that he believes or knows that the defendant is the source of the print. When the examiner offers a weaker, but more scientifically justifiable, conclusion, the evidence is given less weight. However, people do not value the evidence any more or less when the examiner uses very strong language to indicate that the defendant is the source of the print versus weaker source identification language. We also find that cross-examination designed to highlight weaknesses in the fingerprint evidence has no impact regardless of which type of conclusion the examiner offers. We conclude by considering implications for ongoing reform efforts.

There is a probability charge on the power set of the integers that gives probability 1 / p to every residue class modulo a prime p. There exists such a charge that gives probability w to the set of prime numbers iff $$w \in [0,1/2]$$. Similarly, there is such a charge that gives probability x to a residue class modulo c, where c is composite, iff $$x \in [0,1/y]$$, where y is the largest prime factor of c.