Heuristics

1
Heuristics Biases

• Descriptive decision-making cont.
• how people actually make decisions (P Ch 10-16)

2
HEURISTICS

• General rules of thumb
• reduce time and effort to make decision
• reasonably good estimates
• -
• often lead to systematic biases (deviations
• from normatively derived answers)

3
REPRESENTATIVE Heuristic

• judge probabilities by degree to which
• A resembles B
• to what degree does A resemble B?
• -A instance, sample, person
• - B category,population, group

4
Example Representative bias

• Linda is 31 years old,
• single, outspoken
• bright. She majored in
• philosophy and was concerned about social justice
  as a student. She participated in antinuclear
  demonstrations

• Is Linda
• A A bank teller
• B A bank teller who is active in feminist
  movement
• Whats wrong with B?
• (conjuctive fallacy)

5
Representative bias example cont.. (TK, 1982)

• Whats wrong with B A bank teller
  feminist
• Cant be more likely
• than a bank teller?
• conjuction fallacy

6
Representative bias example cont..

• Why did defendant leave scene of crime?
• Which more probable?
• -left scene
• -left scene for fear of
• being accused of
• murder

7
Representative bias example cont.

• Whats more probable?
• General war between US Russia?
• or
• War triggered by third
• country such as Pakistan, Iraq, Libya

8
WHY?

• As amount of detail in scenario increases,
• its probability decreases but its
• REPRESENTATIVENESS and hence
• its apparent likelihood may increase
• (Tversky Kahneman, 198298)

9
Why are representative biases so pervasive?

• more details.gtless probable but more
• PLAUSIBLE
• law of small numbers
• hot hand, gamblers fallacy
• ignore base rate information
• ignore regression to mean
• (praise pilotsgt poorer performance!)

10
So what?

• PSY EXPLANATIONWHY experts so often wrong

11
How to AVOID representative bias?

• Dont be misled by detailed scenarios
• Pay attention to base rates
• Remember, chance is NOT self-correcting!
• Dont misinterpret regression towards mean