Statistical Evidence: How to Help Jurors Understand and Use It Properly

Article excerpt

No matter how skillfully expert witnesses and counsel present potentially bewildering numbers, jurors' psychological aspects must be considered

THE USE of statistical evidence in a jury trial poses specific problems for the parties and the attorneys. This is so in both civil and criminal cases. The effective communication of statistical evidence can be of critical importance to the jury's impression of the case. Statistical evidence in civil cases might involve business concepts, such as market share in an antitrust dispute, or the analysis of the racial or age makeup of the workforce in an employment discrimination case. Mathematical evidence can be important in professional negligence cases that involve engineering specifications, or product liability disputes in which there is exposure to a toxic agent alleged to have caused an illness or injury.

Jurors bring individual beliefs and understandings to the courtroom, whether correct or not, about the use and importance of statistical evidence. These attitudes are the backdrop that must be considered by litigators when shaping their cases for presentation to a jury.

JURORS' UNDERSTANDING OF STATISTICS

Prospective jurors typically understand very little about statistics. Many people have a fear of numbers, and their anxiety causes them to view those who are comfortable with numbers as nerdy or different. "Math geeks" often are ridiculed and mocked. This causes people who are comfortable with numbers to be hesitant to admit it.(1)

When considering how prospective jurors process statistics, it is important to remember that people who are less comfortable with numbers tend to personalize an event more than do those who have a greater understanding of probabilities. If people are uncomfortable with numbers, they are likely to underestimate drastically the existence of coincidence while giving very little weight to statistical evidence on the same subject. In other words, they will perceive causal relationships where none actually exist.

Most people tend to understand probability in a non-mathematical sense and infer plausibility and/or possibility from a mathematical probability. Peter Sedlemeier notes that human beings were not designed to make decisions based on mathematical rules, and as a result, human judgment is often incorrect. One of the ways that human beings deal with statistical problems is to apply heuristics to help them in their decision-making process. These heuristics cause biases or cognitive illusions that might lead to flawed conclusions.(2)

Heuristics are rules of thumb people use to help them simplify the decision-making process. They are processes that save time and effort. Heuristics are an extension of a person's gut reaction and are derived from personal experiences with similar tasks or problems. People rely on heuristics because they believe that the process provides them with reliable outcomes, although that may not always be the case.

One type of heuristic is known as the availability heuristic. It involves the ease with which one can come up with an example of the occurrence of a similar event. If someone has heard of a disease being caused by exposure to a chemical and has a pre-existing notion that many diseases are caused by such exposures, the likelihood that this potential juror will believe the evidence of causation increases. Availability also means that one type of outcome is easier to visualize than an alternative outcome. That is, it is easier to believe that the plaintiff's illness was caused by the chemical than to believe that there is no explanation for the fact that the illness has developed and/or that each person may be susceptible to a random chance of contracting the same illness. The ability to imagine an event's occurrence also makes it more likely in the mind of the decision-maker, even if there is no statistical basis to support that conclusion.(3)

Another psychological concept that impacts a person's ability to use statistics effectively is known as hindsight bias. …