judgement and probabilities

Question 1

What is a judgement?

Answer 1

Calculating the likelihood of events using incomplete information
you give likelihood to options

Question 2

what is decision making?

Answer 2

For judgement, you give likelihood to options - then use decision making to choose the option.

Question 3

Hit

Answer 3

Positive result if you have disease

Question 4

Miss

Answer 4

Negative result if you have disease

Question 5

False alarm

Answer 5

Positive result if you don’t have disease

Question 6

Correct rejection

Answer 6

Negative result if you don’t have disease

Question 7

Bayes Theorem

Answer 7

Bayes’ Theorem is a formula used to update the probability of a hypothesis based on new evidence. It shows how prior beliefs are adjusted in light of observed data to produce a revised (posterior) probability.

Question 8

what is the equation for bayes theorem?

Answer 8

1. Start with the prior information
2. Multiply by the likelihood
3. Divide by the marginal probability (how likely the second finding is)
4. The result is the posterior ( your updated belief about A after seeing B)

Question 9

what is the posterior?

Answer 9

your updated belief about A after seeing B

The probability of event A given that event B has occurred.

Question 10

what is the marginal probability?

Answer 10

how likely the evidence B is overall

Question 11

what is the prior?

Answer 11

Your initial beliefs about A

Question 12

what is the likelihood?

Answer 12

“How likely the evidence is, assuming A is true”

Question 13

Odds ratio hypothesis

Answer 13

This is for comparing two hypothesis ( having the disease vs not having the disease)

Question 14

Prior odds

Answer 14

ratio of probability for one hypothesis over another before seeing the data

belief in H₁ vs. H₂ before seeing data.

Question 15

Likelihood ratio

Answer 15

ratio of probability for data given, hypothesis 1 vs hypothesis 2. ( dividing them by each other)

how much more likely the data is under H₁ than H₂.

Question 16

posterior odds

Answer 16

ratio of probability for hypothesis 1 vs hypothesis 2 given the data

how much more likely H₁ is than H₂ after seeing the data.

Question 17

What is the formula for odds ratio bayes theorem?

Answer 17

Posterior odds = prior odds (H1/h2) x likelihood odds ( H1/H2)

Question 18

base rate neglect

Answer 18

people often forget about the base rate in the judgements

Question 19

What is the Lawyer/Engineer problem designed to test?

Answer 19

How people use (or fail to use) base rate information when making judgments under uncertainty.

Question 20

What were the base rates in the two conditions of the study?

Answer 20

Condition 1: 70 Lawyers, 30 Engineers

Condition 2: 30 Lawyers, 70 Engineers

Question 21

What did 90% of people guess Jack’s profession was?

Answer 21

Engineer — based on the description, not the base rate.

Question 22

What mistake did participants make in their judgment about jack?

Answer 22

They ignored or discounted the base rate and relied too much on representativeness — how much Jack “sounded like” an engineer.

Question 23

What does it mean to ignore the base rate?

Answer 23

You’re acting as if each outcome is equally likely to begin with, rather than considering the actual proportions in the group.

Question 24

Was Jack selected in a biased way?

Answer 24

❌ No — he was randomly selected from the group, so the base rate should have mattered in the judgment.

Question 25

Do people reject or discount base rate information in this task?

Answer 25

They discount it — they still know it’s there but don’t give it enough weight in their decision.

Question 26

when med students had to say how likely person has a disease, how many ignored the base rate?

Answer 26

45% - they said that 95% chance of the person having the disease

Question 27

Why is the real answer closer to 2%, of the person having the disease?

Answer 27

Out of 1000 people: 1 person truly has the disease (likely tests positive). ~50 people will falsely test positive (5% of 999). So: 1 1 + 50 = 1 51 ≈ 2 % 1+50 1 ​ = 51 1 ​ ≈2%

Question 28

Bank teller problem ~ Linda is 31 years old, single, outspoken & very bright. She majored in philosophy. As a student, she was deeply concerned with issues of discrimination and social justice, and also participated in anti-nuclear demonstrations” – Is Linda: 1. A bank teller 2. A bank teller active in the feminist movement? which answer are people more likely to state?

Answer 28

Many choose statement (2), despite (1) being inclusive of statement (2)

Question 29

what fallacy does the bank teller problem illustrate?

Answer 29

Conjunction fallacy – mistaken assumption that probability of conjunction of two events > probability of one of them

Question 30

what is the conjunction fallacy?

Answer 30

The conjunction fallacy happens when people think that two things together are more likely than just one of them alone — which is logically impossible.

Question 31

why is conjunction fallacy a fallacy?

Answer 31

Because in probability, the chance of A and B can never be higher than the chance of just A or just B.

Question 32

What causes the conjunction fallacy?

Answer 32

Representativeness heuristic — people choose what “sounds right” or fits a stereotype, rather than what’s statistically likely.

Question 33

What’s the criticism of the conjunction fallacy?

Answer 33

Sometimes, people might value precision or specificity over pure probability. They may prefer a more detailed answer, even if it's statistically less likely.

Question 34

Why might people ignore redundant information, like "bank teller," in the conjunction fallacy?

Answer 34

They may think that because "bank teller" is mentioned in both options, it’s implied to be true. So, they focus on the extra details (e.g., feminist), which makes the second option feel more specific.

Question 35

what might explain peoples answers in the banker teller question more than conjunction fallacy?

Answer 35

The conjunction fallacy might not always be irrational — people may not be ignoring logic, but rather prioritizing detail and richness in the story, which can feel more informative or accurate.

Question 36

Representative heuristic

Answer 36

Assume object/individual belongs to specific category because it is representative

Question 37

Availability heuristic

Answer 37

Frequencies of events estimated by ease of memory retrieval, e.g., estimate probability of contracting disease based on number of people you know with disease.

Question 38

What did Oppenheimer (2004) show about the Availability Heuristic and whether it always applies?

Answer 38

The effect can be reversed — for example, people might choose a non-famous surname as more common than a famous one, despite the famous name being more readily available in memory.

Question 39

Why did participants choose the non-famous surname more often?

Answer 39

The availability of the famous name might be reduced because people are only recalling instances of a specific individual, not the entire group of people with that famous surname.

Question 40

What are some criticisms of heuristics?

Answer 40

Vaguely defined: It's not always clear exactly when or how specific heuristics apply. Lack of specificity: Doesn't define when specific heuristics should be used. Not always biased: It’s not necessarily biased processing, just poor or incomplete information. Lack of theory: The list of heuristics doesn’t equate to a cohesive theory of human judgment.

Question 41

Dual process theory - what are the two systems?

Answer 41

1. System 1 – fast, automatic, effortless, implicit 2. System 2 – slow, serial, effortful, controlled

Question 42

which system is more accurate?

Answer 42

Often System 1 is used – heuristics! – Emphasises System 1 as not optimal – i.e., prone to errors System 2 is more correct but requires more effort

Question 43

What are Fast and Frugal Heuristics?

Answer 43

Simple decision-making rules that allow rapid processing with little information, leading to correct decisions most of the time, but with a risk of errors.

Question 44

What’s the main trade-off with Fast and Frugal Heuristics?

Answer 44

There’s a trade-off between time and accuracy — they help you make fast decisions, but might not always be the most accurate.

Question 45

What’s the "Take the Best, Ignore the Rest" heuristic?

Answer 45

A decision rule where you choose the best option based on one key piece of information and ignore the rest.

Question 46

What are the 3 rules in the "Take the Best, Ignore the Rest" approach?

Answer 46

Search rule: Find relevant information (e.g., "Do I know this city?" or "Does it have a cathedral?"). Stopping rule: Stop searching once you find an answer (e.g., “If I know one city but not the other, I’ll stop”). Decision rule: Choose based on the best-known option (e.g., “Choose the city I know”).

Question 47

What is the Recognition Heuristic?

Answer 47

This heuristic involves choosing the recognized option when making a decision (e.g., if you recognize one city but not the other, choose the recognized one).

Question 48

How does the Recognition Heuristic work in practice?

Answer 48

Example: Which city is bigger, New York or Guangzhou? Most people would choose New York, simply because they recognize it more (familiarity bias).

Question 49

what will students pick when they are asked which two cities are bigger or more north?

Answer 49

US students were more likely to choose the German city they recognized 90% of the time. But this raises the question: Is it truly recognition driving the choice, or are other factors at play?