Course outline
Module 1
Module 1: Introduction to Heuristics
Introduction to Heuristics
Knowledge check
Q1. What is a heuristic in decision-making?
- A. A formal mathematical proof that guarantees the optimal answer
- B. A mental shortcut that simplifies judgment and usually produces a reasonable answer quickly ✓
- C. A statistical test used to confirm hypotheses
- D. A rule that people always apply consciously and deliberately
Why: Heuristics are efficient mental shortcuts that reduce cognitive effort. They usually work well enough but can lead to systematic errors, which is why they are central to the study of biases.
Q2. Which heuristic describes judging the likelihood of an event by how easily examples come to mind?
- A. Anchoring and adjustment
- B. Representativeness
- C. Availability heuristic ✓
- D. Affect heuristic
Why: The availability heuristic, identified by Tversky and Kahneman, leads people to overestimate the frequency of events that are vivid or easily recalled, such as plane crashes after media coverage.
Q3. A person estimates a home's value starting from its listing price and adjusts only slightly from there. Which heuristic is most clearly at work?
- A. Availability heuristic
- B. Anchoring and adjustment ✓
- C. Recognition heuristic
- D. Gambler's fallacy
Why: Anchoring and adjustment occurs when an initial reference value, here the listing price, strongly influences the final estimate, and adjustments away from that anchor are typically insufficient.
Q4. Judging that someone is a librarian because they are quiet and wear glasses, ignoring how common librarians are in the population, illustrates which heuristic?
- A. Representativeness heuristic ✓
- B. Availability heuristic
- C. Anchoring heuristic
- D. Sunk cost heuristic
Why: The representativeness heuristic involves judging probability by how closely something resembles a stereotype or prototype, often neglecting base rates such as how many librarians exist overall.
Q5. Why do heuristics exist in human thinking?
- A. Because people have unlimited time and information to analyze every decision
- B. Because they eliminate all errors in judgment
- C. Because the mind has limited time and processing capacity, so shortcuts allow fast, adequate decisions ✓
- D. Because they are only used by experts in specialized fields
Why: Human cognitive resources are limited, and real-world decisions often require quick responses with incomplete information. Heuristics provide efficient approximations, trading some accuracy for speed and practicality.
Module 2
Module 2: Availability Heuristic
Availability Heuristic
Knowledge check
Q1. After watching several news reports about plane crashes, a person begins to believe that flying is far more dangerous than driving. Which heuristic best explains this judgment?
- A. Representativeness heuristic
- B. Availability heuristic ✓
- C. Anchoring and adjustment
- D. Gambler's fallacy
Why: The availability heuristic leads people to judge the likelihood of an event by how easily examples come to mind. Vivid, widely reported plane crashes are highly memorable, so they inflate the perceived risk of flying, even though driving is statistically far more dangerous.
Q2. Which of the following is most likely to be overestimated because of the availability heuristic?
- A. The frequency of common, everyday causes of death such as heart disease
- B. The frequency of rare but dramatic causes of death such as shark attacks ✓
- C. The average height of adults in one's country
- D. The number of letters in a typical English word
Why: Dramatic events like shark attacks receive heavy media coverage and are emotionally memorable, making them easy to recall. This ease of recall causes people to overestimate their frequency relative to mundane causes like heart disease, which are statistically far more common.
Q3. A student thinks that words starting with the letter K are more common in English than words with K in the third position. Why might this belief arise?
- A. Words starting with K are actually more common than words with K in the third position
- B. Words starting with a letter are easier to recall and search for mentally, so they seem more frequent ✓
- C. The student has read a dictionary that only lists words beginning with K
- D. Third-position letters are harder to pronounce
Why: Tversky and Kahneman found that people judge words starting with a given letter as more frequent than words with that letter in the third position. This is because it is easier to retrieve words by their initial letter, so retrieval ease is mistaken for actual frequency, which is the availability heuristic at work.
Q4. After a friend's house was burglarized, a homeowner suddenly becomes convinced that their neighborhood has a dangerous crime wave, even though local crime statistics have not changed. What best explains this shift in judgment?
- A. Confirmation bias alone
- B. The availability heuristic, since the recent vivid event makes burglary seem more common ✓
- C. The base rate fallacy, since the homeowner ignored population size
- D. Loss aversion, since the homeowner fears losing property
Why: The recent, emotionally vivid burglary is easy to recall, so the homeowner judges burglary as more frequent than the unchanged statistics show. This is a classic availability heuristic effect, where salience and recency distort probability estimates.
Q5. Why do people who recently experienced a natural disaster often overestimate the chance of another disaster occurring soon afterward?
- A. Because disasters are caused by the same underlying process that repeats every year
- B. Because the vivid memory of the recent disaster makes similar events seem more likely ✓
- C. Because insurance companies have raised their premiums
- D. Because people always expect the worst outcome regardless of experience
Why: A recent disaster is highly vivid and emotionally salient, so it comes easily to mind when people estimate future risk. This availability makes another disaster seem more probable than the objective base rate would justify, illustrating the availability heuristic.
Module 3
Module 3: Representativeness Heuristic
Representativeness Heuristic
Knowledge check
Q1. Linda is 31, single, outspoken, and was a philosophy major who cared deeply about social justice. Which is more likely: (A) Linda is a bank teller, or (B) Linda is a bank teller and active in the feminist movement?
- A. Linda is a bank teller
- B. Linda is a bank teller and active in the feminist movement ✓
- C. Both are equally likely
- D. Neither can be judged from the description
Why: This is the classic conjunction fallacy. People choose option B because the added details make Linda seem more representative of a feminist activist. But the conjunction of two events can never be more probable than either event alone, so option A is actually more likely.
Q2. A coin is flipped 6 times. Which sequence is most likely to occur: (A) H-H-H-H-H-H, (B) H-T-H-T-T-H, or (C) All sequences of 6 flips are equally likely?
- A. H-H-H-H-H-H
- B. H-T-H-T-T-H
- C. All sequences are equally likely ✓
- D. Sequences with more tails are more likely
Why: Every specific sequence of independent fair coin flips has the same probability, 1/64. People judge H-T-H-T-T-H as more likely because it looks more random and thus more representative of a coin's behavior, but this intuition reflects the representativeness heuristic rather than actual probability.
Q3. A hospital has a large and a small maternity ward. About 50% of all babies born are boys. Over a year, which ward is more likely to record more days where over 60% of births are boys?
- A. The large ward
- B. The small ward ✓
- C. Both wards are equally likely
- D. Neither ward would have such days
Why: Small samples fluctuate more widely around the true average, so extreme proportions are far more likely in a small ward. People tend to ignore sample size because the 50% base rate seems representative of both wards. This is the representativeness heuristic's neglect of sample size.
Q4. A man is described as shy, meticulous, and fond of order and detail. Is he more likely to be (A) a librarian or (B) a farmer?
- A. A librarian ✓
- B. A farmer
- C. Equally likely
- D. The description provides no basis for judgment
Why: People match the description to their stereotype of a librarian and judge that match as a strong indicator. However, farmers vastly outnumber librarians in most populations, so the base rate strongly favors farmer. Neglecting base rates in favor of how well a description fits a stereotype is a hallmark of representativeness.
Q5. A student is told that a random person has been described as having a 'gentle soul and a love of poetry,' and that the population is 70% engineers and 30% poets. What is the most accurate way to judge the chance this person is a poet?
- A. Judge it mainly by how well the description fits a poet
- B. Ignore the description and use only the 30% base rate
- C. Combine the base rate with the description using Bayes' theorem ✓
- D. Assume the probability is 50% since the description is ambiguous
Why: The best approach integrates prior probability (base rate) with the diagnostic value of the evidence through Bayes' theorem. Relying only on representativeness ignores the base rate, while ignoring the description discards useful information. Combining both gives the most accurate estimate.
Module 4
Module 4: Anchoring and Adjustment
Anchoring and Adjustment
Knowledge check
Q1. In the anchoring and adjustment heuristic, what does the 'anchor' refer to?
- A. A final decision that people are forced to commit to
- B. An initial value or reference point that influences subsequent estimates ✓
- C. A random number that is ignored when making judgments
- D. The most recent piece of information a person has received
Why: The anchor is the starting value, whether self-generated or externally provided, that people use as a reference point. Estimates then tend to be adjusted away from it, but these adjustments are typically insufficient, so final judgments remain biased toward the anchor.
Q2. Tversky and Kahneman (1974) asked participants to estimate the percentage of African countries in the UN after spinning a wheel of fortune. What did they find?
- A. Participants ignored the wheel result and gave accurate estimates
- B. Estimates were strongly influenced by the random wheel number, even though participants knew it was irrelevant ✓
- C. Participants gave higher estimates only when the wheel number was above 50
- D. The wheel had no effect because participants recognized the randomness
Why: Median estimates were pulled toward the random number from the wheel (e.g., 10 led to about 25%, while 65 led to about 45%). This demonstrated that even arbitrary, clearly irrelevant anchors can significantly shape numerical judgments.
Q3. Which of the following best describes the 'insufficient adjustment' phenomenon?
- A. People adjust too far away from the anchor in every case
- B. People stop adjusting from the anchor before reaching a plausible estimate ✓
- C. People never consider the anchor at all once they have more information
- D. People adjust equally from high and low anchors
Why: Insufficient adjustment means that people start from an anchor and move toward a more reasonable answer, but they stop too early. As a result, their final estimate remains closer to the anchor than it should be.
Q4. A salesperson first shows a customer a $2,000 jacket before showing a $500 jacket. How does anchoring likely affect the customer?
- A. The customer will judge the $500 jacket as more expensive than it is
- B. The customer will judge the $500 jacket as cheaper, since $2,000 serves as a high reference point ✓
- C. The order of display has no effect on perceived value
- D. The customer will refuse to buy either jacket
Why: The $2,000 price serves as an anchor, making the $500 jacket appear relatively inexpensive by comparison. This is a common real-world application of anchoring in pricing and negotiation.
Q5. Which strategy is most effective for reducing the influence of anchoring on your judgments?
- A. Relying only on your first intuition to avoid overthinking
- B. Deliberately generating reasons why the anchor might be wrong and considering alternative values ✓
- C. Choosing the most extreme anchor available to counteract bias
- D. Making decisions quickly under time pressure
Why: Actively considering alternatives and questioning the anchor, sometimes called 'consider the opposite,' encourages more thorough adjustment. Research shows this reduces anchoring effects, whereas quick decisions and extreme anchors tend to increase bias.
Module 5
Module 5: Confirmation Bias
Confirmation Bias
Knowledge check
Q1. Which of the following best describes confirmation bias?
- A. The tendency to remember recent events more vividly than older ones
- B. The tendency to search for, interpret, and recall information in a way that supports one's existing beliefs ✓
- C. The tendency to estimate the likelihood of events based on how easily examples come to mind
- D. The tendency to anchor judgments to an initial piece of information
Why: Confirmation bias is the tendency to favor information that confirms what we already believe, while giving less weight to evidence that contradicts it. It affects how we search for, interpret, and remember information.
Q2. A person who believes a certain diet works reads only articles praising it and skips studies that find no benefit. Which bias is most clearly at work?
- A. Availability heuristic
- B. Hindsight bias
- C. Confirmation bias ✓
- D. Base rate neglect
Why: Selectively seeking out supporting evidence while ignoring contradictory evidence is a hallmark of confirmation bias. The person's existing belief shapes which information they consume.
Q3. Which strategy is most effective at reducing confirmation bias when evaluating a hypothesis?
- A. Looking only for examples that support the hypothesis
- B. Trying to actively falsify the hypothesis by seeking disconfirming evidence ✓
- C. Asking friends who already agree with you
- D. Relying on your gut feeling about whether the idea seems right
Why: Actively seeking evidence that could prove the hypothesis wrong counters the natural tendency to only look for confirmation. This approach, associated with Karl Popper's falsifiability, forces a more rigorous test of the belief.
Q4. In Wason's 2-4-6 task, participants were told the sequence 2, 4, 6 follows a rule and had to discover it. Many participants repeatedly tested sequences like 8, 10, 12 that fit their guessed rule. What did this demonstrate?
- A. Participants were lazy and did not try hard enough
- B. Participants tended to test only cases that would confirm their hypothesis, rather than cases that could disprove it ✓
- C. Participants could not perform basic arithmetic
- D. Participants were overly skeptical of the experimenter
Why: The 2-4-6 task showed that people generally pursue positive tests that confirm their hunch. The actual rule was simply 'any increasing sequence,' so testing sequences that would have violated their guessed rule would have revealed it quickly.
Q5. Why is confirmation bias particularly problematic in everyday reasoning?
- A. It only affects people with low intelligence
- B. It makes people feel more confident in beliefs that may be wrong, and can entrench mistaken views over time ✓
- C. It causes people to forget everything they learn
- D. It prevents people from making any decisions at all
Why: Because confirmation bias filters evidence in favor of existing beliefs, it can inflate confidence in false ideas and make them resistant to correction. It affects people across all levels of intelligence and education.
Module 6
Module 6: Overconfidence and Calibration
Overconfidence and Calibration
Knowledge check
Q1. What is the term for systematically believing that your own judgments or predictions are more accurate than they actually are?
- A. Hindsight bias
- B. Overconfidence bias ✓
- C. Anchoring effect
- D. Availability heuristic
Why: Overconfidence bias refers to the tendency to overestimate the accuracy of one's own beliefs, judgments, or predictions. Hindsight bias is the tendency to see past events as more predictable than they were, anchoring is over-relying on an initial piece of information, and the availability heuristic is judging likelihood by how easily examples come to mind.
Q2. In calibration research, what does it mean for a person to be well calibrated?
- A. They always give the correct answer on factual questions
- B. Their stated confidence levels match the actual proportion of their answers that turn out to be correct ✓
- C. They express high confidence in all of their beliefs
- D. They refuse to give estimates when uncertain
Why: Calibration measures how well subjective probabilities match objective outcomes. If someone says they are 80% confident across many answers, a well-calibrated person should be correct about 80% of the time. Accuracy alone does not establish calibration.
Q3. In a classic study, people asked to answer trivia questions and rate their confidence typically showed which pattern?
- A. Confidence matched accuracy almost exactly
- B. Confidence was systematically lower than accuracy
- C. Confidence was systematically higher than accuracy ✓
- D. Confidence was unrelated to accuracy
Why: In many studies (such as those by Lichtenstein and Fischhoff), people who said they were 100% sure were often wrong a notable share of the time. Confidence commonly exceeds accuracy, which is the basic signature of overconfidence.
Q4. Which technique is most likely to reduce overconfidence in a judgment?
- A. Writing down reasons why your initial estimate could be wrong ✓
- B. Making your estimate more quickly
- C. Relying more heavily on a single vivid example
- D. Avoiding any feedback on past performance
Why: Considering reasons your judgment might be wrong, sometimes called considering the opposite, encourages a search for disconfirming evidence and widens the range of plausible outcomes. Speed, vivid single examples, and lack of feedback all tend to worsen overconfidence.
Q5. Asked to give a 90% confidence interval for a quantity (such as a country's population), what typically happens?
- A. The true value falls inside the interval about 90% of the time
- B. The true value falls inside the interval far less often than 90% of the time ✓
- C. The true value falls inside the interval more than 99% of the time
- D. The interval is always wide enough to contain the answer
Why: Studies of interval estimates consistently find that people's ranges are too narrow, so the true value lands within them much less often than the stated 90%. This narrowness of confidence intervals is a common demonstration of overconfidence in estimation.
Module 7
Module 7: Debiasing Strategies
Debiasing Strategies
Knowledge check
Q1. Which debiasing strategy involves asking yourself what evidence would prove your current belief wrong?
- A. Anchoring adjustment
- B. Considering the opposite ✓
- C. Base rate normalization
- D. Reference class forecasting
Why: Considering the opposite requires actively generating reasons why your initial judgment could be mistaken, which counteracts confirmation bias by forcing attention to disconfirming evidence.
Q2. A manager estimates a software project will take 6 months because that is how long her most optimistic team member predicted. Which bias is most directly at work, and which strategy would help?
- A. Availability bias; seek out vivid counterexamples
- B. Anchoring bias; generate an independent estimate before hearing others' figures ✓
- C. Sunk cost fallacy; ignore past expenditures
- D. Hindsight bias; keep a decision journal
Why: The team member's prediction serves as an anchor. Forming an independent estimate before exposure to others' numbers reduces the pull of that anchor on the final judgment.
Q3. What is the main purpose of a pre-mortem analysis?
- A. To review what went well after a project finishes
- B. To imagine a future failure and work backward to identify its causes before committing to a plan ✓
- C. To calculate statistical probabilities of project success
- D. To assign blame after a decision has gone wrong
Why: A pre-mortem assumes the project has failed and asks team members to explain why. This surfaces risks that optimism or groupthink would otherwise suppress.
Q4. Why is reference class forecasting useful for reducing the planning fallacy?
- A. It asks you to rely on your personal memory of similar tasks
- B. It bases the forecast on the actual outcomes of comparable past projects rather than on the specifics of the current plan ✓
- C. It eliminates uncertainty by modeling every variable
- D. It requires the forecaster to double all time estimates arbitrarily
Why: Planners tend to focus on the unique features of their project, which feel controllable. Using the distribution of outcomes from similar past projects grounds the forecast in observed reality.
Q5. Which of the following is an example of using structured decision aids to reduce bias?
- A. Trusting your gut when information is incomplete
- B. Using a checklist that requires you to list evidence for and against an option before choosing ✓
- C. Deciding quickly to avoid overthinking
- D. Relying on the most experienced person's intuition
Why: Checklists force systematic consideration of multiple factors and disconfirming evidence, reducing reliance on whatever comes to mind first.