Ii) Six Heurestics Re Probability Assessment Under Uncertainty/Risk

i) representativeness or similarity or stereotyping (an area of concern is "insensitivity to prior probability of outcomes", ie one of the factors that has no effect on representativeness but has a major effect on probability is prior probability, or base rate frequency of outcome. When specific evidence is given, prior probabilities are properly utilised; when worthless evidence is given, prior probabilities are ignored)

ii) insensitivity to sample size (when selecting a sample it should be representative of the population under study; this does not depend on the size sample, ie it is independent of sample size. On the other hand, the smaller sample size has a greater chance of having a larger variation than a large sample size

"...Intuitive judgments are dominated by sample proportion and are essentially unaffected by the size of the sample, which plays a critical role in the determination of the actual posterior odds. In addition, intuitive estimates of posterior odds are far less extreme than the correct values. The underestimation of the impact of evidence has been observed repeatedly in problems of this type. It is labeled conservatism..."

Daniel Kahneman 2012)

iii) misconceptions of chance (it is expected that a sequence of events generated by random process will represent the essential characteristics of that process even when the sequence is short.)

"...A locally representative sequence, however, deviates systematically from chance expectation: it contains too many alterations and too few runs..."

Daniel Kahneman 2012

At times, too much faith is placed in the results of small samples and people grossly over-estimate the replicability of such results. This bias leads to the selection of samples of inadequate size and to over-interpretation of findings.

Another consequence of the belief in local representativeness is a well-known gambler's fallacy, ie after a run of heads in a coin toss activity, people expect an increasing chance of tails to restore the equilibrium. Yet the results of each coin toss are independent of past results and at any deviation are not necessarily corrected.)

iv) insensitivity to predictability (many predictions are insensitive to the reliability of the evidence and to the expected accuracy of the prediction; this violates the normative statistical theory in which the extremes and range of predictions are controlled by considerations of predictability; in general, the higher the predictability, the wider the range of predicted values)

v) illusion of validity (a good fit between the predictable outcome and the input information, ie

"...People predict by selecting the outcome (for example, an occupation) that is most representative of the input (for example, the description of a person)......their prediction depends primarily on the degree of representativeness (that is, the quality of the match between selected outcome and the input) with little or no regard for the factors that limit predictive accuracy. Plus, people expressed great confidence in the prediction that a person is a librarian and given a description of his personality which matches the stereotype of librarians, even if the description is scanty, unreliable or outdated..."

Daniel Kahneman 2012

This can apply to selection interviews

"...The internal consistency of a pattern of inputs is a major determinant of one's confidence in predictions based on these inputs......Highly consistent patterns are often the most observed in the input variables..."

Daniel Kahneman 2012)

vi) misconceptions of regressions (regression towards the mean; this leads to over-estimating the effectiveness of punishment and the under-estimating the effectiveness of reward ‐ see earlier)

Bias

Availability

. Availability (assessing the frequency of a class or the probability of an event by the ease with which instances or occurrences can be brought to mind; it is judgmental; it is affected by factors other than frequency and probability, such as

i) bias is due to be retrievability of instances (a group whose instances are easily retrieved will appear more numerous than a class of equal frequencies whose instances are less retrievable)

ii) salience (the more visual an event, the greater the impact; recent events are likely to be more readily available than earlier appearances

iii) biases due to effectiveness of a search set (different tasks elicit different search sets, eg comparing the frequency of abstract words (thought, love, etc) and concrete words (door, water, etc) -in written English, we think of context)

iv) biases of imaginability (when assessing the frequency of a class whose instances are not stored in the memory but can be generated according to a given rule; generally one generates several instances and evaluates frequency or probability by the ease with which the relevant instances can be constructed - but this does not necessarily reflect actual frequency or likelihood)

v) illusory correlation (bias that occurs in the judgment of the frequency with which two events co-occur; tend to markedly overestimate; extremely resistant to contradictory data; the importance of the strength of the associative bond between the events, ie if it is strong, it is concluded that the events are frequently paired)