What is a likelihood ratio, and how is it used to express forensic strength?

What is a likelihood ratio, and how is it used to express forensic strength?

• A. The ratio of the probability of observed evidence under two competing hypotheses; higher ratios indicate stronger support for one hypothesis over the other.
• B. It measures the speed of analysis.
• C. It calculates the age of the evidence.
• D. It represents the cost of the examination.

Answer: (A)

A likelihood ratio is a way to quantify how much more likely the observed evidence is if one hypothesis is true than if another hypothesis is true. It expresses forensic strength by comparing probabilities: LR = P(E | H1) / P(E | H2), where E is what was observed and H1 and H2 are competing explanations (for example, the suspect committed the crime vs. someone else did). A higher LR means the evidence fits H1 much better than H2, providing stronger support for that hypothesis. If the LR is around 1, the evidence doesn’t distinguish well between the hypotheses; if it’s less than 1, it supports the alternative hypothesis more. Other options describe aspects like analysis speed, age of the evidence, or cost, which are not measures of how strongly the evidence supports one hypothesis over another.

A likelihood ratio is a way to quantify how much more likely the observed evidence is if one hypothesis is true than if another hypothesis is true. It expresses forensic strength by comparing probabilities: LR = P(E | H1) / P(E | H2), where E is what was observed and H1 and H2 are competing explanations (for example, the suspect committed the crime vs. someone else did). A higher LR means the evidence fits H1 much better than H2, providing stronger support for that hypothesis. If the LR is around 1, the evidence doesn’t distinguish well between the hypotheses; if it’s less than 1, it supports the alternative hypothesis more.

Other options describe aspects like analysis speed, age of the evidence, or cost, which are not measures of how strongly the evidence supports one hypothesis over another.