Can a person be found guilty based purely on statistical evidence?

Question

Imagine that there is a home care worker Alice who takes care of some great number of outpatients. Some significant proportion of them have reported thefts, although none of them suspect Alice. Since her patients are elderly and not particularly alert, they're not very useful as witnesses and in no single situation is there definitive proof that it is she that stole from them.

For the sake of this hypothetical, let's say that thefts in general are common in this area, but that Alice's patients are far more likely to be stolen from than others.

So for each individual crime there is reasonable doubt as to Alice's guilt, but the totality of the cases are such that it is extremely unlikely that she didn't commit at least several acts of theft (although we cannot say for certain which ones).

Is there a name for situations like these? And if it's not too broad of a question: how are they handled?

Answer 1

Is there a name for situations like these?

Yes: Circumstantial evidence.

In R v Xu, Justice Katz explains how it works:

[163] In a circumstantial case, the Court must look to the combined effect of a number of independent items of evidence when considering each charge. While each separate piece of evidence must be assessed as part of the inquiry, the ultimate verdict on each charge will turn on an assessment of all items of evidence viewed in combination. The underlying principle is that the probative value of a number of items of evidence is greater in combination than the sum of the parts. The analogy that is often drawn is that of a rope. Any one strand of the rope may not support a particular weight, but the combined strands are sufficient to do so. The logic that underpins a circumstantial case is that the defendant is either guilty or is the victim of an implausible, unlikely series of coincidences.

[164] When assessing the evidence in a circumstantial case, it is not sufficient to evaluate each separate strand of evidence in isolation and then stop. Having considered each strand of evidence separately, it is necessary for the decision-maker to then stand back and assess the cumulative effect of all of the different strands of evidence. Consideration of the onus and standard of proof only occurs at the second stage of the process. The individual strands of evidence do not have to be proved beyond reasonable doubt. The onus and standard of proof only comes into play once the combined weight of all of the strands of evidence is being considered.

If Alice is the only care worker for the patients who have reported theft, the cumulative effect of the totality of the individual strands of evidence could well be enough to prove guilt beyond reasonable doubt (whereas none of the strands alone could be sufficient).

But if there are other care workers who could do that, the probability of guilt slashes down proportionally, so no real prospect for Alice to be convicted.

Answer 2

I will disagree with @GreenDrake's circumstantial evidence answer. Yes, you can totally be convicted on it alone, but to even be charged for a crime, you need to be charged for a specific crime. Alice isn't being charged for a theft, she's being charged for e.g. the theft of Mrs. Doe's wallet on April 1, 2022. If there's other evidence, even circumstantial evidence (e.g. Alice went to a casino straight after leaving Mrs. Doe), then an expert witness statistician could give testimony, but if there's absolutely no evidence whatsoever linking Alice to a specific crime, any non asleep defense attorney will get the charge summarily dismissed.