Forensic science cheat sheet

Chain of custody

Document who collected, transferred, stored and examined an item, so its identity and handling can be checked.

Record each transfer rather than relying on memory.

Observation and inference

An observation records what was measured or seen. An inference proposes an explanation for those findings.

“A fibre was recovered” differs from “this person was present”.

Comparison and controls

Compare questioned material with suitable reference samples. Controls help identify contamination or problems in the procedure.

A negative control checks whether the process introduced a signal.

Evidence strength

Evidence may support one explanation more than another. Its strength depends on methods, uncertainty and alternative explanations.

A match alone does not establish when or how material was transferred.

Transfer and persistence

Material can transfer directly or indirectly, and can be lost or redistributed over time. Presence, source and the activity that caused deposition are separate propositions.

Finding a person’s DNA does not by itself establish the timing or circumstances of contact.

Screening and confirmation

A screening procedure narrows possibilities; a confirmatory examination addresses a more specific proposition using validated methods. The meaning of a result depends on the method and its known limitations.

Describe what the method detects rather than calling every positive result an identification.

Likelihood ratios

A likelihood ratio compares the probability of the evidence under two specified propositions. It is not the probability that either proposition is true.

LR = P(evidence | proposition 1) ÷ P(evidence | proposition 2).

Validation and error

Validation evaluates a method under defined conditions, including reproducibility and error. Error-rate estimates depend on the task, sample population, decision rules and treatment of inconclusive results.

A laboratory study’s error rate should not be presented as an exact probability for every case.

Worked example: conditional probability

Suppose a finding has probability 0.8 under one proposition and 0.2 under another. Its likelihood ratio is 0.8 ÷ 0.2 = 4, for those two propositions and assumptions.

“Four times as probable under proposition 1” does not mean “an 80% probability of guilt”.

Common mistake: transposing the conditional

P(a result | a source) and P(a source | a result) are different quantities. Moving from evidence strength to a conclusion also requires prior information and alternative explanations.

Keep the conditioning statement visible whenever you describe a probability.

Check your understanding

Does LR = 10 mean a 90.9% probability of guilt?

No. A likelihood ratio compares probabilities of evidence under specified propositions; it does not supply prior odds or decide guilt.

Curriculum connections

Sources