1. Reasoning & Problem Solving Kimberley Clow kclow@uwo.ca http://instruct.uwo.ca/psychology/130

2. Outline  Simple Decisions  Formal Logic Errors  Attributions  Algorithms vs. Heuristics Representaiveness Availability Anchoring  Other Effects

3. Simple Decisions  Decisions about physical differences Psychophysics  Subjective experience of magnitude is not identical to the physical magnitude of the stimulus Perception is not the same thing as Sensation Just Noticeable Difference (JND)  By how much energy two stimuli must differ for us to notice the difference

4. Distance Effect  Which is brighter? A lighter or a flashlight A lighter or a spotlight  The greater the distance between two stimuli being compared, the faster the decision that they differ

5. Different Effects  Which dot is higher? Easier decision for A, B, C, or D?  Symbolic Comparisons  Semantic Congruity Effects

6. Formal Logic and Reasoning  Syllogisms A syllogism (or categorical syllogism) is a three- statement logical form First two parts are a premise (which are taken to be true), the third part states a conclusion based on those premises  Goal: to understand how different kinds of premises can be combined to yield logically true conclusions, and to understand what combinations of premises lead to incorrect conclusions  All A are B. All B are C. Therefore all A are C.

7. Conditional Reasoning  A conditional is an “if-then” statement. The “if” part is the antecedent. The “then” part is the consequent.  Example: If pregnant, then a female. Being pregnant is the antecedent. Being female is the consequent.

8. Inferences

9. Form Errors  Using an invalid form denying the antecedent affirming the consequent  Illicit conversions Assuming that a conditional is actually a bi-conditional  that “if p then q” implies “if q then p.”

10. Search Errors  Confirmation Bias Tendency to look for evidence that confirms a hypothesis  modus ponens Failure to look for evidence that could possibly falsify a hypothesis  modus tollens Example  The Wason Selection Task

11. Wason Selection Task

12. What About Uncertainty?  Think about understanding behaviour, where causes are not clear or certain  Imagine a scenario… A young woman, Jill, carrying a stack of papers trips and the papers fall all over the place. A young man, Jack, helps her retrieve all of her papers.  Why did Jack help Jill?

13. Basic Terms  Attribution the process through which we come to understand the causes of others’ behaviour as well as the causes of our own behaviour  Internal Attribution inferring that a particular behaviour demonstrated by an individual was due to dispositional causes  External Attribution inferring that the individual’s behaviour was caused by some other factor than his or her dispositions (e.g., situational causes)

14. Covariation Principle  Explain behaviour according to 3 factors Consistency  How does the person react to the same stimulus/event on different occasions? Distinctiveness  How does the person respond to other stimuli/events that are similar? Consensus  How do other people react to the same stimulus/event?

15. Attribution Principles  Discounting Principle the role of a given cause in producing a given effect is discounted if other plausible causes are also present  Augmentation Principle If both a factor that facilitates the behaviour and a factor that inhibits the behaviour are present, we assign added weight to the facilitative factor

16. Fundamental Attribution Error  The tendency to underestimate the role of situations overestimate the role of dispositions

17. Algorithms vs. Heuristics  Algorithm specific rule or solution procedure guaranteed to give the correct answer if followed correctly  Heuristic a "rule of thumb" procedure quick, easy, efficient not always appropriate

18. Representativeness Heuristic  When people estimate the probability of an event by How similar the event is to the population of events it came from  Prototype matching Whether the event seems to be similar to the process that produced it

19. Category Membership  People belong to multiple social groups simultaneously Age, sex, race, nationality, occupation, hobbies, personality, etc.  How we perceive people as belonging to social categories depends on their perceived representativeness Subtyping occurs if a person does not fit with pre-existing stereotypes

20. Base Rates  Marie is very quiet and studious. In her spare time, she takes women’s courses at the university. It is most likely that Marie is  A librarian  A feminist  A librarian and a feminist  Do we use base rate information? Lawyer vs. Engineer description (#1)

21. Perceptions of Chance  Which super-lotto ticket would you prefer? 7, 12, 18, 24, 33, 45 or 1, 2, 3, 4, 5, 6  The representativeness heuristic biases our perceptions of chance (#2) e.g., gambler’s fallacy

22. Availability Heuristic  We base our judgements of frequency on how available things are in our memory Biased by what we pay attention to or code into memory  Events that are common are usually easier to think of than events that are less common because we have had more experience with them

23. Why Does This Occur?  Some events are easier to retrieve from memory e.g., words with “r” (#3)  Some events are easier to imagine e.g., shark attack vs. falling airplane (#4)  Exposure to a biased sample of events Selective exposure to events False Consensus Effect

24. Forms of the Availability Heuristic  The Saliency Bias The salience or prominence of information determines whether we notice it and how much we pay attention to it  Exerts greater influence on our judgement  Egocentric/Self-Centered Bias The tendency for people to overestimate their responsibility for jointly produced outcomes  Who does more housework?

25. Anchoring  When making a judgement, we begin with an initial value, guess, or starting point called the anchor, and then we adjust our estimate from that anchor  We don’t adjust away from anchors sufficiently

26. Self-Enhancement Biases  Self-Serving Bias the tendency to attribute our positive outcomes to internal causes but our negative outcomes to external factors  Unrealistic Optimism Bias the tendency to predict more optimistic future outcomes for ourselves than for others  Better-Than-Average-Bias the tendency to rate ourselves as better than our average peer  leadership question (#5)

27. The Simulation Heuristic  Involves a mental construction or imagining of possible outcomes a forecasting of the possibilities of how some event will turn out A forecasting of how an event might have turned out under different circumstances  Imagine possible outcomes if Germany had developed the atomic bomb before the U.S.?

28. The Undoing Heuristic  A version of the simulation heuristic involving the undoing of some outcome by changing the events that led up to it  Uses Counterfactual Reasoning When a line of reasoning deliberately contradicts the facts of what happened Asking “what if”?

29. Hindsight Bias  The after-the-fact judgment that some event was very likely to happen, even though it wasn’t predicted beforehand  A bias in which otherwise plausible outcomes are now less easy to imagine than the outcome that actually happened

30. Why Use Heuristics?  Certain limitations force us to use heuristics over algorithms Limited domain knowledge or insufficient mental models  Naïve Physics Limitations in processing resources  People stereotype more when they are cognitively busy e.g., dual task  People stereotype more when they are low on resources Night vs. Day people in early and late experiments

31. Naïve Physics

32. Solutions…

33. Limited Resources  Please answer the following: 8 x 7 x 6 x 5 x 4 x 3 x 2 x 1 = ?  What if instead you saw: 1 x 2 x 3 x 4 x 5 x 6 x 7 x 8 = ?  Limited working memory capacity forces us to “guestimate” rather than compute  Most people guess bigger answers when they see the first over the second version anchoring

34. Brain Damage and Reasoning  Participants were No brain damage (normal) People with frontal lobe damage People with temporal lobe damage  All solved transitive inference problems: a > b, b > c, Is a > c?  All also worked on a Matrices Test

35. Sample Matrices Test