WEEK 3: Heuristics & Biases Flashcards
Define Representativeness! Provide example
Probability are evaluated by degree to which A is representative of B, i.e., by degree A resembles B.
Ex: Steven is shy, helpful, need for order and structure. Is he a librarian, farmer, or lawyer?
What is prior probability/base-rate frequency, and can you provide example how people are insensitive towards it?
Prior probability/base-rate frequency of outcome is a legitimate statistical outcome of the particular example. People will ignore given prior probability and choose to determine outcome by degree A is representative of B.
Are people’s assessment of similarity between sample and population dependent on given sample size?
No. If assessed by representativeness, the judged probability of sample statistic is independent of sample size.
E.g., Probability of obtaining an average height of 6ft was assigned same value for samples of 1000, 100, and 10
Define posterior probability and provide your own example, fitting the definition.
Posterior probability is the probability of an event or hypothesis, after some observed evidence or data.
E.g., Believe it might rain tomorrow, but uncertain. You check weather forecast, and reassess probability of it raining (posterior probability)
Adjusting estimate of likelihood of something being true, based on what you see or learn (posterior = later/afterwards)
How do people apply the representativeness heuristic rule when given posterior odds?
People are biased by viewing simply the sample proportion, rather than size of proportion.
E.g., Urn holds 2/3 R, & 1/3 W. Which case most likely supports this probability with 4R/1W & 12R/8W.
Subject guessed 4r/1w by simply the larger proportion of reds
What is the critical misconception of chance?
People expect randomly generated events will represent essential characteristics of process (even when sequence is short.)
E.g., Roulette wheel bound to hit black after long run of reds
How do people use representativeness and be insensitive towards predictability?
People soley focus on representativeness, e.g., description, without consideration of reliability, accuracy, or even essential predictability, to make predictions.
What is the illusion of validity? How is this even further bias emphasised but in fact false?
The illusion of validity is the unwarranted confidence produced by the good fit of A (input info) to B (predicted outcome). If high internal consistency is present, one is more confident. In fact, high consistent patterns are redundant and correlated (taken as indicator for prediction) and redundancy causes decreased accuracy
What is the concept of regression? How do people misconceive it?
If one selects two scores, X and Y, of the same distribution. And if first selection (x) deviates from mean by k units, second score (y) will deviate from mean by less than k units. And vice versa.
People develop wrong intuition and
1. Don’t expect regression where it is bound to occur (consecutive flight training)
2. Develop false causal explanation (due to verbal praise/punishment)
What is the biggest issue with use of representativeness to determine uncertain situations?
The use of representativeness is an issue when individuals use similarity and probability in exactly the same way. Similarity and probability are affected by completely different factors, thus leading to an issue when people take on this approach to judge probability.
Define the availability heuristic rule and name the possible biases from using the availability heuristic (4).
The availability heuristic rule is the tendency people have of assessing frequency of a class/probabiliity of an event by ease which instances/occurrences can come to mind. E.g., risk of heart attack by recalling one’s acquaintance.
Possible biases/errors include: the retrievability of instances, the effectiveness of available search set, bias of imaginability, and illusory correlation (degree of associative bond between two events).
What are two possible forms of bias in retrievability? Explain the difference
The two forms include familiarity and salience.
Familiarity is the retrieval of familiar events (e.g., comes to mind more easily, easier to remember, etc.), thus making a class appear more prominent over the other class.
Salience is the retrieval of events that are most prominent to oneself (salient) and thus making it appear more likely, e.g., witness car crash and believing in subjective probabilty of car crash occuring.
Define the bias due to effectiveness of search set?
Judge uncertain events by class that is most easily “searchable” instances
Give a real life example and an experimental example of biases due to imaginability.
- Group of 10 numbers, how many different combinations
possible (2 < k < 8). Ease of constructing 2 combinations. - Camping; ease of imagining risk situation creating appearance highly risk / cannot imagine risk situation thus appearing unlikely of risk
Illusory correlation varies on degree associative bond is strong, T/F
T/F. E.g., Eyes associated with suspiciousness
