Common Biases

Biases:

1. Availability Heuristic: Ease of recall (based on vividness and recency)

a. Because it was more difficult to recall certain examples, subjects often saw themselves as less assertive, for example even though they listed many examples.

b. We assume that our available recollections are truly representative of the larger pool of events that exists outside of our range of experience. As decision makers we need to understand when intuition will lead us astray so that we can avoid the pitfall of selecting the most mentally available option.

2. Representativeness Heuristic: Ignoring background information relevant to a problem such as the base rate

c. Insensitivity to sample size- when responding to problems dealing with sampling, people often use the representativeness heuristic and ignore the issue of sample size. Market research uses consumers’ bias to their advantage in ads such as “Four out of five dentists recommend sugarless gum to their patients.’

d. Misconceptions of chance: Our inappropriate tendency to assume that random and non-random events will balance each other out. Many fall victim to the ‘law of small numbers’. They believe that sample events should be far more representative of the population from which they were drawn than simple statistics dictate. Scientists often grossly overestimate the degree to which empirical findings can be generalized to the general population.

e. Regression to the mean: Basic statistics tell us that any extreme performance is likely to regress to the mean over time. Many individuals typically assume that future outcomes will be directly predictable from past outcomes. Thus we tend to naively develop predictions based on the assumption of perfect correlation with past data.

f. The Conjunction Fallacy: A conjunction (a combination of two or more descriptors) cannot be more probable than a single component descriptor when the conjunction appears more representative...