1. Thinking: Concept Formation Concept formation: identifying commonalities across stimuli that unite them into a common category Rule learning: identifying commonalities requires learning ‘rules’ about which stimulus attributes are essential to category membership. How are rules learned: Two hypos 1.Associative learning – simple s-r connection between presence of attribute and category membership 2.Hypothesis testing – learner actively formulates possible rules and applies them Hypo testing generally pursued as either conservative focusing (where attributes are manipulated methodically to see which is relevant) or focused gambling (where one attribute is singled out and testing while ignoring others)

2. What makes something a member of the category bird? Rule: flying=bird problems: passive; exceptions Hypo testing: Flying things are birds – right? Conservative focus: Isolate flying variable Focus gambling: assume flying true, wait for exceptions.

3. Category representation How are categories stored and represented in the head? Classical view: categories separated by defining features – Problem: people rarely use or even know defining features of category – Problem: typicality effects Probabilistic view: categories defined by common features or most frequently occurring features of category members. Degree of ‘family resemblance’ determines typicality of category members Exemplar view: category defined by a particular or few typical members. Argued to retain more information about category features compared to probabilistic view. For example: average bird (probabilistic view) may sing, but exemplar shows that large birds –no sing; smaller/medium birds –sign.

4. Thinking: Reasoning Reasoning: manipulating internal representations to arrive at new knowledge or to draw new conclusions. Two forms: Syllogistic reasoning: based on ‘accepted’ premises upon which conclusions are drawn. Task it to decide if conclusions are valid or not Valid conclusion: must be only conclusion possible based on relationships described in premises. Must be necessitated by premises, not just possible based on premises

5. Syllogistic reasoning Premise: statement assumed to be true for sake of argument, not necessarily empirically true Premise: All boys are athletes Premise also usually expresses a relationship between certain concepts, so boys are related to athletes in that all boys are a member of the category athletes.

6. Syllogistic reasoning Conclusion: to be valid must be necessitated by the premises. Must be only possible conclusion drawn base on relationships expressed in premises. Conclusion: a valid conclusion cannot just be reasonable or plausible based on premises, it must be necessary.

7. Syllogistic reasoning P1: All boys are athletes P2: All athletes are muscular C: All boys are muscular Valid: Use Venn Diagrams to determine.

8. Syllogistic reasoning P1: All boys are athletes P2: All muscular people are athletes C: All boys are muscular people Valid? See website for more reasoning problems

9. Framing Effects in Decision Making Imagine that the U.S. is preparing for the outbreak of an unusual disease which is expected to kill 600 people. Two alternative programs have been proposed. Assume that the exact scientific estimate of the consequences of the program is as follows: If Program A is adopted, 200 people will be saved. If Program B is adopted, there is a 1/3 probability that 600 people will be saved and a 2/3 probability that no people will be saved. Which of the two programs would you favor? Imagine the identical situation with the following choices: – If program C is adopted, 400 people will die. – If program D is adopted, there is a 1/3 probability that nobody will die, and a 2/3 – probability that 600 people will die. Which of the two programs would you favor?

10. Decision making “Outbreak” problem shows that decision- making not purely rational process. Other factors affecting decisions. Framing effects: context within which problem is set Regret: choice that is perceived as involving greater or less future emotional pain Certainty effects: overvaluing of certainty can bias decision in one direction or another