Thinking - Judgement And Decision Making

Question 1

What is Bayes’ Theorem used for in decision-making?

1) Evaluating the frequency of events
2) Inverting conditional probabilities to find the probability of a cause given its effect
3) Identifying the most representative category
4) Estimating probabilities using heuristics

Answer 1

Inverting conditional probabilities to find the probability of a cause given its effect

Question 2

What is the primary reason humans deviate from normative reasoning?

1) Lack of mathematical skills
2) Reliance on heuristics as cognitive shortcuts
3) Over-reliance on memory effects
4) Inability to understand probabilities

Answer 2

Reliance on heuristics as cognitive shortcuts

Question 3

What does the representativeness heuristic involve?

1) Evaluating the likelihood of an event based on ease of recall
2) Judging probabilities based on typicality or similarity to a prototype
3) Ignoring probabilities to focus on vivid examples
4) Using mathematical probabilities to make decisions

Answer 3

Judging probabilities based on typicality or similarity to a prototype

Question 4

What was the key finding in the “Linda problem”?

1) People correctly estimated conjunction probabilities
2) Most participants committed the conjunction fallacy
3) Base rates were accurately incorporated into judgments
4) Specific details led to less biased decisions

Answer 4

Most participants committed the conjunction fallacy

Question 5

What does the gambler’s fallacy assume?

1) Future outcomes in random events are influenced by past outcomes
2) Probabilities in random events remain constant
3) People are good at estimating randomness
4) The likelihood of streaks increases with time

Answer 5

Future outcomes in random events are influenced by past outcomes

Question 6

What is the availability heuristic?

1) A method to estimate probabilities using base rates
2) Judging event likelihood based on ease of retrieving examples from memory
3) The assumption that all probabilities are equal
4) Overestimating the frequency of high-probability events

Answer 6

Judging event likelihood based on ease of retrieving examples from memory

Question 7

What error did Tversky & Kahneman find in the taxi cab study?

1) Participants accurately used base rates in their judgments
2) Participants overestimated the probability based on witness accuracy
3) Participants ignored the probability of false alarms
4) Participants focused on random chance

Answer 7

Participants overestimated the probability based on witness accuracy

Question 8

What percentage of medical students in Casscells et al. (1978) neglected the base rate?

1) 95%
2) 80%
3) 45%
4) 18%

Answer 8

45%

Question 9

How does frequency framing affect base rate neglect?

1) It increases neglect of base rates
2) It reduces base rate neglect compared to probability framing
3) It eliminates decision-making biases entirely
4) It has no impact on reasoning

Answer 9

It reduces base rate neglect compared to probability framing

Question 10

Why do people often get availability heuristic problems wrong?

1) They rely on statistical data
2) Media coverage influences their perception of likelihood
3) They lack understanding of randomness
4) They prefer logical reasoning over intuition

Answer 10

Media coverage influences their perception of likelihood

Question 11

What did Lichtenstein et al. (1978) study in relation to the availability heuristic?

1) Judged frequency of lethal events
2) Random event probabilities
3) Errors in medical diagnoses
4) Statistical methods for reasoning

Answer 11

Judged frequency of lethal events

Question 12

What was Tversky & Kahneman’s (1974) finding about words starting with “K”?

1) Words with “K” in the third position were more frequent but less available
2) People overestimated the frequency of words starting with “K”
3) People accurately estimated the distribution of “K” in words
4) Word frequency had no impact on judgments

Answer 12

Words with “K” in the third position were more frequent but less available

Question 13

What is the conjunction fallacy?

1) Believing two events together are less likely than one alone
2) Believing two events together are more likely than one alone
3) Overestimating probabilities based on base rates
4) Ignoring statistical probabilities in random events

Answer 13

Believing two events together are more likely than one alone

Question 14

What key factor influences the representativeness heuristic?

1) Statistical accuracy
2) Base rate prevalence
3) Similarity to mental prototypes
4) Frequency of occurrences

Answer 14

Similarity to mental prototypes

Question 15

What was the probability of the cab being blue in the taxi cab study?

1) 0.80
2) 0.50
3) 0.41
4) 0.15

Answer 15

0.41

Question 16

What does the gambler’s fallacy incorrectly assume about random sequences?

1) Patterns occur in completely random events
2) Random events have no impact on each other
3) Future outcomes will remain consistent with base rates
4) Probability depends on past outcomes

Answer 16

Probability depends on past outcomes

Question 17

What decision-making error occurs due to media coverage?

1) Representativeness heuristic
2) Base rate neglect
3) Availability heuristic
4) Conjunction fallacy

Answer 17

Availability heuristic

Question 18

What was Cosmides & Tooby’s key finding about base rate neglect?

1) Probability framing eliminates errors in judgment
2) Frequency framing reduces base rate neglect
3) Probability framing improves normative reasoning
4) Framing has no effect on base rate neglect

Answer 18

Frequency framing reduces base rate neglect

Question 19

What does base rate neglect often lead to in medical decisions?

1) Overestimation of rare conditions
2) Accurate probability estimates
3) Reduction in diagnostic errors
4) Equal weighting of base rates and test results

Answer 19

Overestimation of rare conditions

Question 20

What common theme underlies heuristics like availability and representativeness?

1) They rely solely on mathematical reasoning
2) They are purely memory-based
3) They simplify complex problems but lead to biases
4) They are infallible in high-stakes decisions

Answer 20

They simplify complex problems but lead to biases