← PSY 1: Introduction to Psychology

Unit 13: Judgment, Decision Making, Heuristics, and Biases

The mental shortcuts that make snap judgments possible, and the systematic ways those same shortcuts lead smart people astray.

8 topics · 30 questions

Each topic is a path, not a menu: work down it in order and every question builds on the one above. Click any of them to watch the answer draw itself.

Heuristics as Mental Shortcuts

  1. How it worksHow does a heuristic trade a little accuracy for a lot of speed by substituting an easy question for a hard one?
  2. Going furtherWhat happens to a heuristic's accuracy when the situation it's applied to no longer matches the situation it evolved to handle?
  3. Common mistakeWhy isn't relying on a heuristic the same thing as reasoning badly on purpose?
Your turn1 of 2
Asked how risky a proposed investment is, a person quickly answers based on a gut feeling rather than working through the actual numbers, arriving at a confident answer within seconds. A student assumes this quick answer must come from some kind of shortcutted version of the same careful calculation. How does a heuristic actually trade a little accuracy for a lot of speed?

The Availability Heuristic

  1. How it worksHow does the availability heuristic judge an event's frequency by how easily examples of it come to mind?
  2. Worked exampleFind why news coverage of plane crashes, which are rare, makes flying feel far more dangerous than driving, which kills far more people per year.
  3. Common mistakeWhy isn't how memorable an event is the same thing as how often it actually happens?
Your turn1 of 2
Sharks kill roughly 9 people per year worldwide, while falling coconuts are estimated to kill roughly 111 people per year. Find how many times more people coconuts kill than sharks do, even though shark attacks feel far more available in memory.

The Representativeness Heuristic

  1. How it worksHow does the representativeness heuristic judge likelihood by how much something resembles a category's stereotype?
  2. Worked exampleFind why judging someone a librarian based on personality alone is a mistake when librarians make up only 1 in 8000 workers.
  3. Common mistakeWhy isn't a description that sounds like a category proof that the category is the more likely one?
Your turn1 of 2
In a workforce of 29071 people, 1 in every 8490 workers is a librarian. Find how many librarians there are among the 29071 workers.

Base Rates and Natural Frequency Trees

  1. How it worksHow does drawing a tree of natural frequencies, out of 1000 people, turn an abstract base-rate problem into something you can just count?
  2. Worked exampleFind the chance a person testing positive actually has a disease that affects 1 in 1000 people, given a test that is 99 percent accurate.
  3. Going furtherWhat happens to that same positive-test probability once the disease's base rate rises from 1 in 1000 to 1 in 10?
Your turn1 of 2
A disease affects 1 in 1545 people. A test for it is 96 percent accurate, both for correctly flagging someone with the disease and correctly clearing someone without it. Find the percent chance that a person who tests positive actually has the disease.

The Conjunction Fallacy

  1. How it worksHow does a vivid, coherent story make a conjunction of two events feel more probable than either event alone?
  2. Worked exampleFind why the combined probability of two events can never be higher than the probability of either event by itself.
  3. Going furtherWhat happens to the conjunction fallacy's grip when people are asked for frequencies out of 100 people instead of a single probability?
  4. Common mistakeWhy isn't a more detailed, specific story ever more probable than a less detailed version of the same story?
  5. Ties togetherHow does the conjunction fallacy connect back to the representativeness heuristic that drives it?
Your turn1 of 2
Event A has a probability of 0.433, and event B has a probability of 0.407. Find the highest possible probability that both A and B happen together, which can never exceed the smaller of the two individual probabilities.

Anchoring and Adjustment

  1. How it worksHow does an initial anchor, even an arbitrary one, pull a final estimate toward itself?
  2. Worked exampleFind why a first offer of 500 dollars in a negotiation tends to anchor the final price higher than a first offer of 300 dollars would.
  3. Common mistakeWhy isn't anchoring something that only affects people who don't know any better?
Your turn1 of 2
A negotiation without any anchor would typically settle at 479 dollars. A first offer of 1219 dollars is made instead, and final prices in these situations tend to land about 0.48 of the way from the unanchored price toward the anchor. Find the resulting anchored final price.

Loss Aversion and the Value Function

  1. How it worksHow does prospect theory's value function bend more steeply for losses than for gains around a reference point?
  2. Worked exampleFind why a coin flip offering a 50 percent chance to win 100 dollars against a 50 percent chance to lose 100 dollars feels like a bad bet to most people.
  3. Worked exampleFind why most people reject a coin flip for a 50 percent chance to gain 150 dollars against a 50 percent chance to lose 100 dollars, despite its positive expected value.
  4. Common mistakeWhy isn't a rational decision maker, under prospect theory, someone who values a dollar gained the same as a dollar lost?
  5. Going furtherWhat happens to the shape of the value function's curve as an amount moves further away from the reference point?
Your turn1 of 2
A coin flip offers a 50 percent chance to win 233 dollars against a 50 percent chance to lose 118 dollars. Find the expected value of this bet.

The Limits of Introspection

  1. How it worksHow do studies where people choose between identical items reveal that stated reasons are often invented after the choice, not the cause of it?
  2. Common mistakeWhy isn't your own explanation for your behavior automatically the true cause of it?
  3. Going furtherWhat happens to a person's confidence in a self-reported reason when the researcher secretly swaps the item they chose for a different one?
  4. Going furtherWhat happens when a split-brain patient's left hemisphere invents a fluent, false verbal reason for an action actually caused by the isolated right hemisphere?
  5. Ties togetherHow does the unreliability of introspection connect to why eyewitnesses can feel certain about a memory that's actually false?
Your turn1 of 2
In a classic study, shoppers chose which of several identical pairs of stockings they preferred and then confidently explained their choice by citing differences in texture or weave, even though all the pairs were truly identical. A student assumes people's stated reasons for a choice must generally be an accurate report of what actually caused that choice. What do studies like this reveal about stated reasons for a choice?