• Shuffle
Toggle On
Toggle Off
• Alphabetize
Toggle On
Toggle Off
• Front First
Toggle On
Toggle Off
• Both Sides
Toggle On
Toggle Off
Toggle On
Toggle Off
Front

### How to study your flashcards.

Right/Left arrow keys: Navigate between flashcards.right arrow keyleft arrow key

Up/Down arrow keys: Flip the card between the front and back.down keyup key

H key: Show hint (3rd side).h key

A key: Read text to speech.a key

Play button

Play button

Progress

1/26

Click to flip

### 26 Cards in this Set

• Front
• Back
 System 1: Intuition: Fast, automatic, effortless, implicit, emotional and common. System 2: Reasoning: Slow, conscious, effortful, logical and less common. Can System 1 and System 2 Thinking operate at the same time? Both can operate at the same time and be in conflict with each other Normative Decision Making Perfect (ideal) decision making is referred to as “normative” decision making. We evaluate all of the information to correctly derive the best solution. Rational Decision Making: 6 Step Process 1. Accurately define the problem 2. Identify the criteria (the qualities needed) 3. Weight the criteria in importance 4. Generate alternatives (list of people) 5. Rate each alternative (applicant) on each criterion 6. Compute an optimal decision Bounded Rationality Decisions that are influenced by factors not directly tied to consequences are said to be bounded. Most of the time our judgments are bounded or limited to some extent. Why Bounded Rationality? We lack or ignore important information. We operate under time and/or cost constraints We have a limited memory system (STM) We have difficulty knowing what the optimal choice is It is easier to settle for an acceptable (satisficing) solution rather than the “best” solution. Decision Making Models: Perscriptive Models The goal is to give us the best methods for making optimal decisions. Develop mathematical models (actuarial methods). Decision Making Models: Descriptive Models The goal is to identify our mistakes and help us understand them. Heuristics A heuristic is a simplified strategy for solving problems. They usually give us a “good” solution, but not always the best. Heuristics are automatic. Descriptive model decision making research has identified a number of heuristics. Availability Heuristic We assess the probability of an event by the degree to which the event is available in memory. Emotional and vivid events are more available. Example: What is safer traveling by air or by car? Biases Emanating from Availability Heuristic Ease of recall We judge events that are easy to recall because they are more vivid or recent to be more numerous. Example: Performance appraisal are often weighted towards the most recent behaviors. Biases Emanating from Availability Heuristic Retrievability Are there more words that end in ing than words that have n as the 7th letter? Biased on how our memory structures are organized. Biases Emanating from Availability Heuristic Is marijuana use linked to delinquency? Presumed Associations We tend to over estimate the probability of two events co-occurring based on the number of similar associations we can easily recall. Representative Heuristic We tend to look for traits an individual may have that correspond with previously formed stereotypes. Example: Gender and racial stereotypes in hiring and promotion Biases Emanating from Representativeness Heuristic Mark is finishing his MBA at a prestigious university. He is very interested in the arts. Where is he more likely to take a job? – A. In arts management or B. With a consulting firm Insensitivity to base rates. When assessing the likelihood of events, we tend to ignore base rates if any other information is provided. Biases Emanating from Representativeness Heuristic A large hospital has 45 babies born each day a smaller hospital has 15 babies born each day. In a one year period, which will have more days in which 60% of the babies born were boys? Insensitivity to Sample Size We frequently fail to appreciate the role of sample size. Larger samples are more likely to come closer to the average than small samples. Biases Emanating from Representativeness Heuristic Which sequence is more random? – THTHHTTHT or HHHHTHHHT Misconceptions of Chance We expect a sequence of random events to look random even when the sequence is too short. Gambler’s fallacy: After some bad luck, I’m due. Biases Emanating from Representativeness Heuristic What are the odds the Bengals will make the playoffs next year? Regression to the Mean We ignore the fact that extreme events are likely to regress to the mean on subsequent trials. Biases Emanating from Representativeness Heuristic Linda is 31, single, outspoken, and very smart. She majored in philosophy and is deeply concerned with issues of discrimination. Linda is.. – A. a bank teller – B. a bank teller and active in a feminist movement. The Conjunction Fallacy We falsely judge that two or more events that co-occur are more probable than a more global set of of occurrences. Affect Heuristic Emotional influences that are automatic and maybe out of our awareness. More likely to be used when people are busy or under time constraints. Example: I don’t like her for some reason (she looks like my first wife). Other Biases Anchoring We make estimates for values based upon an initial value and make insufficient adjustments from that anchor. We also access information that is consistent with the anchor. The candidates resume was outstanding, his interview was only average, but he is still my best candidate. Other Biases Which is more likely to occur? – A. Drawing a red marble from a bag with 50% red and 50% white marbles..,, – B. Drawing a red marble seven times in a row from a bag with 90% red and 10% white marbles…, – C. Drawing at least one red marble in seven tries from a bag with 10% red and 90% white marbles.,,, Conjunctive and Disjunctive Event Bias We exhibit a bias towards overestimating the probability of conjunctive events and under estimate the probability of disjunctive events. Other Biases Over Confidence We tend to be overly confident of the infallibility of our judgments when answering moderate to difficult questions. Other Biases The Confirmation Trap We tend to seek confirmatory information for what we think is true and fail to search for nonconfirmatory evidence. Example: WMD’s in Iraq? Other Biases Hindsight and Curse of Knowledge After finding out whether or not an event occurred, we tend to overestimate the degree to which we would have predicted the correct outcome.