Chapter 8 Thinking, Decisions, & Intelligence PDF

Chapter 8: Thinking, Decisions, & Intelligence PSYC 200 Analogical Symbolic Representation Representation Symbolic Representations: Ben throws the ball. The ball is thrown by Ben. Analogical representation...

Chapter 8: Thinking, Decisions, & Intelligence PSYC 200 Analogical Symbolic Representation Representation Symbolic Representations: Ben throws the ball. The ball is thrown by Ben. Analogical representation  Analogical representations Symbolic representation: The spy saw the man with the binoculars  Writing Analogical Symbolic Reality Representati Representati on on Readin Analogical Representation of a Problem  Problem Solving & Decision Making Problem solving – Finding a way around an obstacle to reach a goal. – Building an analogical representation of a problem is the first step to effectively solve the problem. Decision making – A cognitive process that results in the selection of a course of action or belief from several options.  Problem Representation The Buddhist monk problem One morning a Buddhist monk sets out at sunrise to climb a path up the mountain to reach the temple at the summit. He arrives at the temple just before sunset. A few days later, he leaves the temple at sunrise to descend the mountain, traveling somewhat faster since it is downhill. Is there a spot along the path that the monk will occupy at precisely the same time of day on both trips? How do you construct an analogical representation of this problem? How problem representation facilitates problem solving? Unproductive Representation Productive Representation Thinking in terms of Visualize the path of the distance & speed monk ascending and Trying to locate that spot as descending the mountain. if solving a math or physics The paths start at opposite problem—it is not this ends and proceed in complicated. opposite direction. Think of two monks walking in opposite directions along the same path on the same day. Problem Representation: Which of these problems are similar?  Chi, Feltovich, & Glaser (1981). Background – The quality of problem representation influences the ease with which the problem can be solved. – Experts possess domain specific knowledge (or problem schemata) with which solutions to the problems are easily arrived. – “…much of expert power lies in the expert’s ability to quickly establish correspondence between externally presented events and internal models for these events” (p. 123) – Experts represent problem by category (i.e., perceptual  Chi, Feltovich, & Glaser (1981) Purpose To investigate the qualitative differences between the representations of physics problems by experts and novices. To understand the role of categorization in expert problem solving.  Results Novices sorted the problems based on surface structures : the objects (e.g., inclined plane) referred to in the problems, the literal physics terms mentioned in the problems (e.g., friction), the physical configuration described in the problems (e.g., a block on an inclined plane). Experts sorted the problems based on deep structures: physics principles governing the solutions of the problems (e.g., Newton’s second law, conservation of energy)  Results Experts were slower in sorting the problems. Experts spent more time analyzing the problems; they tried to understand the problems before solving the problems. Final remark: Expertise is only an advantage in the expert’s specialty (recall that the chess master was not better than the novice in memorizing random chess positions) Question to think about: What might be a disadvantage of being an expert?  Deductive Reasoning & Problem Representation: Example 1 How you represent (or re-present) a problem affects how (quickly) you solve the problem. Consider the following syllogism: – All A are B – Some B are C – Therefore, some A are C Is the conclusion valid (i.e., is this conclusion always true?) How do you re-present this problem?  Deductive Reasoning & Problem Representation: Example 2 Conditional If P is true, then Q is true. Evidence P is true P is not Q is Q is not true true true Inference Is Q Is Q Is P Is P to be true? true? true? true? drawn How do you re-present this problem?  Logic and Reasoning Some recurring themes: We are often overly influenced by the general world knowledge stored in our memories when making judgments. We are more capable thinking in concrete ways than in abstract ways. We tend to search for evidence that confirms our decisions, beliefs, and hypotheses.  Logic and Reasoning Research generally suggests that people are poor at solving these problems when the problems are presented in an abstract form. When the problems are re-presented in terms of concrete & real-world concepts, people are better at seeing the solutions. Our world knowledge sometimes has prevented us from seeing the pure logic; and sometimes has enabled us to see it.  Deductive Reasoning Deductive reasoning is a type of reasoning which begins with some specific premises that are assumed to be true. Based on the premises, a conclusion is drawn. A conclusion is valid if it follows the principles of logic. Deductive reasoning involves determining whether the conclusion is valid. Two major types of deductive reasoning: – Syllogism – Conditional reasoning (also called propositioning reasoning)  Syllogism A three-statement logical form. The first two parts state the premises or statements taken to be true. The third part states a conclusion based on those premises.  Syllogism In abstract form In concrete form All A are B. All poodles are dogs. All B are C. All dogs are animals. Therefore, all A are C Therefore, all poodles are animals. Syllogism and Venn Diagram  Syllogism and Venn Diagram C Venn diagrams can be B used to determine A whether a conclusion is A=B valid: =C B= C C A All A are B. All B are C. A= B All A are C. All four Venn diagrams yield the same conclusion: All A are C  Validity versus Empirical Truth A valid conclusion does not always have empirical truth. Example: All poodles are animals. This is a All animals are wild. valid Therefore, all poodles conclusion are wild. ! (The 2nd premise is empirically false.)  Validity versus Empirical Truth A premise is an assumption: Assuming that premise A is valid, Assuming that premise B is valid, Then premise C must be valid. But what if one of the initial assumptions is wrong? When doing research, if one of the initial assumptions is wrong, the whole conclusion does not have empirical truth (we are wrong from the beginning).  Invalid Syllogism An invalid syllogism is one that the first two premises are true (or assumed to be true), but the conclusion is false (or is not always true). The following syllogism is invalid, why? All A are B Some B are C. Therefore, some A are C.  Thinking in an Abstract Way More than one Venn diagram can be drawn to represent the first two premises: All A are B. Some B are C. The two Venn diagrams yield two different conclusions. B B A C A C Some A are C. No A are C. No single conclusion can be drawn for the relation between A and C.  Thinking in a concrete way All polar bears are animals. Some animals are white. Therefore, some polar bears are white. (Empirically correct conclusion) All polar bears are animals. Some animals are brown. Therefore, some polar bears are brown. (Empirically incorrect conclusion)  Conditional Reasoning: If P then Q Two parts: 1) A conditional clause - If P (the antecedent), then Q (the consequent) 2) Evidence - P is true (P) - P is not true (not P) - Q is true (Q) - Q is not true (not Q)  Conditional Reasoning Conditional reasoning involves a logical determination of a conclusion (or no conclusion) if one part of the if/then statement is assumed to be true or not true. Conditional If P is true, then Q is true. Evidence P is true P is not Q is Q is not true true true Inference Is Q Is Q Is P Is P to be true? true? true? true? drawn  Thinking in an abstract way Condition If P is true, then Q is true. al Evidence P is true P is not Q is true Q is not true true Name Modus Denying Affirming Modus ponens the the tollens Affirming antecede conseque Denying the nt nt the antecedent consequent Inference Is Q true? Is Q true? Is P true? Is P true? to be Thinking in a concrete way: Example 1 Conditional If you heat ice, it melts. Evidence You heat You do not The ice The ice ice. heat the melts. does not ice. melt. Inference to Does the Does it Do you Do you be drawn ice melt? melt? heat it? heat it? Thinking in a concrete way: Example 1 Conditional If you heat ice, it melts. Evidence You heat You do not The ice The ice ice. heat the melts. does not ice. melt. Inference to Does the Does the Do you Do you be drawn ice melt? ice melt? heat it? heat it? Yes Uncertain Uncertain No  Thinking in an abstract way again Conditiona If P is true, then Q is true l Evidence P is true P is not Q is true Q is not true true Nature of Affirming the Denying Affirming Denying the the antecedent the the consequent Evidence (Modus antecedent consequen (Modus ponens) t tollens) Conclusion Q is true No No P is not true conclusion conclusion Thinking in a concrete way: Example 2 Conditional If you take a sleep pill at 1:00 a.m., you will feel sleepy at 2:00 a.m. Evidence You take a You do You feel You do sleeping not take a sleepy at not feel pill at sleeping 2:00 a.m. sleepy at 1:00 a.m. pill at 2:00 a.m. 1:00 a.m. Inference to Will you Will you Did you Did you be drawn feel feel take a take a sleepy at sleepy at sleeping sleeping 2:00 2:00 pill at pill at a.m.? a.m.? 1:00 1:00 Thinking in a concrete way: Example 2 Conditional If you take a sleep pill at 1:00 a.m., you will feel sleepy at 2:00 a.m. Evidence You take a You do not You feel You do not sleeping take a sleepy at feel sleepy pill at 1:00 sleeping 2:00 a.m. at 2:00 a.m. pill at 1:00 a.m. a.m. Inference to Will you Will you Did you Did you be drawn feel sleepy feel sleepy take a take a at 2:00 at 2:00 sleeping sleeping a.m.? a.m.? pill at 1:00 pill at 1:00 a.m.? a.m.? Conclusion Yes Uncertain Uncertain No  Are people good at conditional reasoning? Modus ponens Affirming the antecedent People are good at inferring the truth of the consequent given evidence that the antecedent is true. Performance was excellent (100% in one study) for the case of modus ponens when the problems were presented in either concrete or abstract form.  Are people good at conditional reasoning? Modus tollens Denying the consequent Rate of making correct inferences for the case of modus tollens ranged from 57% to 77% when the problems were stated in an abstract form. However, when the problem was presented in the form of everyday experience, on average 87.5% people could make a correct conclusion.  The Wason Selection Task The Wason cards are created with the following rules: A card with a vowel on it will have an even number on the other side. Which card or cards would you turn over to obtain conclusive evidence about the rule (i.e., to find out  Diagnosing the problem Conditional: If a card has a vowel on one side, then it has an even number on the other. Evidence E (vowel): Affirming the antecedent (modus ponens) K (not vowel): Denying the antecedent 4 (even): Affirming the consequence 7 (not even): Denying the consequence (modus tollens)  Solving the Wason cards problem Only the modus ponens and modus tollens will yield conclusive evidence about the validity of the rule Therefore, the cards to be turned over are E and 7.  Empirical results of the Wason Selection Task 33% of Wason’s subjects turned over only the E card. Only 4% of subjects turned over both the E & 7 cards. 46% of subjects turned over both the E & 4 cards. Generally, subjects tended to search for positive evidence—evidence that affirms the antecedent and the consequent. This is the confirmation bias (discussed later): People would rather try to confirm or support a Conditional reasoning in everyday life How well do people apply conditional reasoning to solve an everyday problem? Empirical finding: People checked both the modus ponens and modus tollens when the problem to be solved is presented in a concrete form (in this case, people might not be aware that they are actually solving a conditional reasoning problem). Conditional reasoning in everyday life You are given this rule: If a person is drinking beer, then the person must be over 20 years of age. The following cards represent the information of four people drinking in a bar. One side of the card shows the beverage that the person is drinking. The other side of the card shows the age of the person. Which cards will you turn over to check whether the rule is followed? Conditional reasoning in everyday life You are given this rule: If a person is drinking beer, then the person must be over 20 years of age. The following cards represent the information of four people drinking in a bar. One side of the card shows the beverage that the person is drinking. The other side of the card shows the age of the person. Which cards will you turn over to check whether the rule is followed? 73% of the participants selected the correct cards Conditional reasoning in everyday life This problem involves catching an illegal behavior. The problem motivates people to adopt a skeptical attitude. When we become skeptical, we are sensitive to negative evidence (i.e., we are skeptical toward those who violate the law). 73% of the participants selected the correct cards  Two Types of Errors Relating to Conditional Reasoning Form Errors - People assume that: If P, then Q = If Q, then P - The right equation should be: If P, then Q = If not Q, then not P  Two Types of Errors Relating to Conditional Reasoning Search Errors - People tend to search for positive evidence only (unless they become skeptical, then they will pay attention to negative evidence). - The tendency to search for information that supports a conclusion (or a belief) is called a confirmation bias. - People tend to ignore the rules of logics when they are occupied with a confirmation bias.  Type I & Type II Processing Dual-process theory: Distinguish between two types of cognitive processing: Type I processing – Fast & automatic – Requires little conscious attention – E.g., stereotyping, use of heuristics (discussed later) Type II processing – Slow and controlled – Requires focused attention – E.g., think of exceptions to a general rule Inductive or Inductive or deductive ? deductive ? Answer: Inductive Answer: Deductive  Decision making often involves heuristics Heuristic is a “rule of thumb” that provides a best- guess solution to a problem. A general rule or problem-solving strategy that usually produces a correct solution. However, it sometimes leads to errors. Examples: – The representativeness heuristic – The availability heuristic  Representativeness Heuristic If you toss a fair coin six times in a row, which of the following two outcomes is more likely? HHHHHH HHTHTT Most people would think that the second outcome is more likely.  Representativeness Heuristic The representativeness heuristic is a judgment rule in which an estimate of the probability or likelihood of an event is determined by one of two features: 1) how similar the event is to the population of events it came from or 2) whether the event seems similar to the process that produced it (e.g., random process should produce random patterns of results). Definition provided by Psychological Science: – Placing a person or an object in a category if that person or object is similar to one’s prototype for that category.  Representativeness Heuristic In the coin toss example, the population of events are those with a combination of H and T. The result HHTHTT has alterations between heads and tails and thus it resembles the population of random events. The result HHHHHH is an odd combination, the chance of getting this unique result is 1/64. In fact, the combination of HHTHTT is equally unique and the chance of getting it is also 1/64.  Representativeness Heuristic The gambler’s fallacy: If a fair coin toss comes up heads five times in a row, what would you bet on the next toss? heads or tails? HHHHH ? Most gamblers would believe that the next toss would be tails. This is called the gambler’s fallacy.  Representativeness Heuristic The gambler’s fallacy (continued): Gamblers mistakenly believe that the five previous tosses have bearing on the 6th one. HHHHHH is harder to get than HHHHHT. HHHHHT has greater resemblance to the population of events that are the results of a random process. In fact, the result of the 6th toss is independent of the results of the previous tosses.  Base Rates & Representativeness 1) Why are more graduate students first-born than second-born children? 2) Why do more hotel fires start on the first ten floors than the second ten floors? 3) In baseball, are more runners thrown out by pitchers on first base or on second base?  Base Rates & Representativeness 1) Why are more graduate students first-born than second-born children? - Because there are more first-born than second- born children in the population.  Base Rates & Representativeness 2) Why do more hotel fires start on the first ten floors than the second ten floors? - Because many hotels do not have the second ten floors.  Base Rates & Representativeness 3) In baseball, why are more runners thrown out by pitchers on first base than on second base? - because there are more runners on first base than on second base. These questions are difficult to answer because people usually ignore the base rates of events. Who are more likely to develop lung cancer? Smokers or Nonsmokers Percentage distribution of smokers and non-smokers who have developed lung cancer Non- Smokers Total Smokers 75 25 100 Who are more likely to develop lung cancer? Smokers or Nonsmokers Table A Table B Percentage distribution of Percentage distribution of smokers & Non-smokers in smokers & non-smokers the general population who have developed lung Non- Smoker Total cancer smokers s Non- Smoker Total 95 5 100 smokers s 75 25 100 Smokers are more likely to develop lung cancer. There are only 5% of smokers in the general population; but 25% of patients with lung cancer are smokers. Who are more likely to develop lung cancer? Table A Table B Percentage distribution of age Percentage distribution of age and smoker-status in the and smoker-status in lung population cancer patients Non- Smoke Total Non- Smoke Total smoker rs smoker rs s s Young 60 1 61 Young 25 5 30 Older 35 4 39 Older 50 20 70 Total 95 5 100 Total 75 25 100  Base Rates & Representativeness A psychologist wrote the following description of Tom when he was in high school: Tom is highly intelligent, but he is not genuinely creative. Tom needs everything to be orderly and clear, and he likes every detail to be in its appropriate place. His writing is quite dull and mechanical, although he loves corny puns. He sometimes makes up plots about science fiction. Tom has a strong drive for competence. He seems to have little feeling for other people, and he has little sympathy for their problems. He does not actually like interacting with others. Although he is self- centered, he does have a deep moral sense.  Base Rates & Representativeness Now suppose that Tom is a graduate student at a large university. Rank the following nine fields of specialization, in terms of the likelihood that Tom W is now a student in that program. Write 1 for “most likely,” and 7 for “least likely.” Business administration Computer science Engineering Humanities and education Law Medicine Library science Physical & life science Social sciences & social work  Base Rates & Representativeness If we know absolutely nothing about Tom, the best guess is the option that has the highest number of enrollments: “humanities and education” or “ social sciences and social work.” However, the description of Tom had triggered the stereotype for students in computer science and engineering. People most frequently guessed that Tom is a graduate student in computer science or engineering. This suggests that people had made their guesses based on stereotype (or representativeness) rather than on base rates.  Base Rates & Representativeness People made their decisions based on the representative heuristic. However, the use of heuristic could sometimes lead to the right answer. A guess based on stereotype has a better chance of being right than a blind guess.  Availability Heuristic Availability means ease of retrieval. The availability heuristic holds that when people have to make estimates of likelihood or frequency, their estimates are influenced by the ease with which relevant examples can be remembered.  Availability Heuristic Example 1: How reliable is a Japanese car? In this case, you are asked to estimate the frequency of repair required by a Japanese car. Suppose you have a friend who has a Toyota that needs to be repaired frequently. If your major source of knowledge about Japanese cars is your friend’s Toyota, you tend to think that Japanese cars are unreliable. Your bias against Japanese cars comes from a readily retrieved example of your friend’s car.  Availability Heuristic Example 2: What is the ratio of Chevrolets sold to Cadillacs sold? Most people estimate that Chevrolets are 10 or 15 times more numerous than Cadillacs. The actual Chevrolets to Cadillacs ratio is 5:1. The estimation was based on how frequently a Chevrolets/ Cadillacs is seen on the streets.  Availability Heuristic The more frequently people are exposed to a stimulus, the more easily the stimulus is retrieved from memory. Most people who own an expensive car do not use the car on a daily basis. Expensive cars are reserved for special occasions. Cadillacs are parked in garages whereas Chevrolets are driven/parked on the streets. The number of Cadillacs sold is underestimated because they are out of sight, and hence out of mind.  Availability Heuristic Example 3: Is it safer to travel by airplane or by car? People tend to think that travelling by airplane is less safe than travelling by car. The opposite is true. According to statistics, travelling by commercial airliner is 25 times safer than by private car.  Availability Heuristic This bias can be attributed to the factor of salience or vividness of special events. One air crash is more striking than many ordinary car accidents. Salience or vividness overrides frequency of occurrence—base rates are ignored. Right after an air crash, people’s confidence in airplane industry drops drastically. One single incident is enough to ruin the reputation of a whole business.  Availability Heuristic Are the following claims valid? Females have poor math skills. People on welfare are cheaters. Gay people have psychological problems. Can’t tell the validity of the claims before we have some actual data. But even with a full set of data, people with confirmation bias fail to see the big picture.  Confirmation Bias Confirmation bias is the tendency to search for, interpret, and recall information in a way that confirms one’s belief or hypothesis, while giving disproportionately less consideration to alternative possibilities.  Confirmation Bias: Example 1 Number in Each Category Gay Straight Total People People People with 6 8 14 psychological problems People without 54 72 126 psychological problems Total 60 80 140 Focus of Ignored  Hypothetical Information about Sexual Orientation & Psychological Problems Number in Each Category Gay Straight Total People People People with 6 8 14 psychological problems People without 54 72 126 psychological problems Total 60 80 140 6/60 = 8/80 =  Example You have a 2 mixture of symptoms: Headache Memory loss Sensitivity to light Pins & needles sensations in the I have arms and legs migraine. Nausea & vomiting Weakness in the limbs and faces Symptoms of brain tumor Symptoms of migraine Experiment demonstrating confirmation bias in making diagnosis (dangerous!) Medical students and psychiatrists read a case about a 65-year-old-man. They gave a preliminary diagnosis of either Alzheimer’s disease or severe depression. Each person then decided what kind of additional information they would like. 25% of medical students and 13% of psychiatrists selected only the information that was consistent with their original diagnosis. A mixture of symptoms that the patient has: 6 were consistent with Alzheimer’s disease. The patient 6 were consistent with has severe severe depression. depression. Symptoms of Alzheimer’s disease Symptoms of severe depression  Availability Heuristic: A Summary The availability heuristic is used to estimate frequency based on available examples. This estimation is affected by: – Recency of events – Familiarity with the events – Salience of the events Oftentimes, the estimation is accurate. Comparing the representativeness & availability heuristics Representativeness heuristic – Given a specific example (e.g., the profile of an individual), judge the likelihood that the example is a membership of a general category (e.g., the individual is a feminist activist). – The judgement is based on the degree of similarity between the specific case and the general category. Availability heuristic – Given a general category (e.g., air crash), judge the frequency of occurrence of this general category. – The judgement is based on the ease of coming up with a specific example.  Anchoring Bias The tendency to rely on the first piece of information encountered to make a judgment or decision. An anchor serves as a reference point.  Anchoring Bias Group A Group B Question 1 Question 1 The telephone was invented The telephone was invented before or after 1850? before or after 1920? People correctly answered “after.” People correctly answered “Before.” Question 2 Question 2 When was the telephone invented When was the telephone invented (make your best guess if you (make your best guess if you don’t know)? don’t know)? Conclusion: The averageWhen participants estimation were asked was 1870 to make The average an estimation estimation of was 1900 the year the telephone was invented, the initial year that they were asked to consider (1850 or 1920) served as an anchor or reference point.  Framing Effect Highlighting effect: What do you want to highlight?  Framing Effect: Example 1 Sidewalk Sale  Framing Framing Effect: Effect: Example 2 2 Example Two different ways to say the same thing  Intelligence Intelligence is the ability to use knowledge to reason, make decisions, make sense of events, solve problems, understand complex ideas, learn quickly, and adapt to environmental challenges. What is the operational definition of intelligence? It is ridiculously simple: “intelligence is what an intelligence test measures.” What do intelligence tests measure then? The majority of intelligence tests measure the skills that are required to do well in academic work. E.g., abstract reasoning & verbal fluency. The purpose of an intelligence test is to predict academic success.  Measuring Intelligence A brief history: In 1905, Alfred Binet and Theodore Simon in France published a scale (called the Binet-Simon scale) that could be used to identify children that needed special training in school. The test was a success because it was capable of predicting children’s academic performance. This scale measured a child’s mental age. A child with a mental age of 6 performed like the average 6- year-old on the test (but the child’s biological age could be older or younger than six).  Stanford-Binet Intelligence Scale In 1916, Lewis Terman and his colleagues at Stanford University published the Stanford-Binet Intelligence Scale. The test itself was very close to the original Binet- Simon scale. The major difference was in the scoring of the test. The test result was expressed as an intelligence quotient (IQ): The ratio makes it possible to compare the intellectual abilities of children of different ages because the ratio places all children (regardless of age) on the same scale.  Structure of the Wechsler Adult Intelligence Scale (WAIS) The first IQ test for adults was published in 1939 by David Wechsler. Compared to the Stanford-Binet test, WAIS incorporated two major innovations: 1) Less dependent on verbal IQ – It has separate scores for verbal IQ, performance (non-verbal) IQ, and full-scale(total) IQ. 2) Has a new scoring scheme – Scoring is based on the normal distribution and standard deviation. – The mean of the distribution is set at 100, and the standard deviation is 15. Structure of the Wechsler Adult Intelligence Scale (WAIS) The normal distribution of intelligence If your IQ score = 115, it means: Your IQ is one standard deviation higher than the average of the adult population. Your IQ is higher than 84% of people You are labelled as high average  Summary of the history of IQ tests Test Name Innovation Binet-Simon Scale Introduces the concept of mental age. Stanford-Binet Introduces the concept of Intelligence Scale intelligence quotient: a ratio of mental age to chronological age. Wechsler Adult First intelligence test for adults. Intelligence Scale Has verbal and non-verbal (WAIS) subscales. Test results are presented as a normal distribution.  Do intelligence tests have adequate reliability? Reliability = consistency of measurement A reliable test yields similar scores upon repetition. Reliability is computed as a correlation coefficient. IQ tests usually have a correlation coefficient in the 0.90s IQ Tests  Do intelligence tests have adequate validity? Validity = the ability to measure what it was designed to measure Most intelligence tests were designed to measure abilities required for academic success. Intelligence tests can predict school performance fairly well. In this sense, intelligence tests have high validity (they measure what they are meant to measure). The correlations between IQ scores and school grades typically range from 0.40 to 0.50. One study with a big sample size reported a correlation of 0.70. Do intelligence tests have adequate validity? Why do the correlations between IQ scores and school grades are not in the ranges of 80s and 90s? School grades are affected by other factors, not just intellectual abilities. For example: – Motivation – Diligence – Personality – Conscientiousness – Self control/regulation – Social life/support – Relationship  Correlations between IQ and schooling Correlations between IQ and school grades range between 0.40 and 0.50. Correlations between IQ and years of schooling range between 0.60 and 0.80. The causal link between IQ and years of schooling is bidirectional – Those people with higher IQ tend to stay longer in school. – People who stay longer in school will develop better intellectual abilities, of course.  Do intelligence tests predict vocational success? The correlation between IQ and occupational attainment is 0.37 (averaging across many studies). People who score high on IQ tests are more likely than those who score low to end up in high-status jobs. The correlation between IQ and income is 0.21 (averaging across many studies) The correlation between IQ and job performance is 0.50, (or actually in the 0.30s before statistical corrections). As a whole, the correlation between IQ and vocational success is moderate. Hiring decisions should not be made based on IQ testing alone. Emotional Intelligence Emotional intelligence is a good predictor of: Quality of Workplace social School grades performance relationship  Emotional intelligence Emotiona consists of four l abilities Intelligen Managing one’s emotions ce Using one’s own emotions to guide thoughts and actions Recognizing other people’s emotions Understanding emotional language Giftedness: Developmentally Advanced Definition of giftedness: – Exceptional high ability with respect to intellect, creativity, or the skills associated with specific disciplines. Operational definition of giftedness: – Two or more standard deviations above the mean on a standardized, individually administered test of cognitive abilities. Gifted children may demonstrate outstanding abilities in more than one area. However, they may also have disabilities in other areas. Giftedness: Development ally Advanced Paradoxical Negative Effects of Giftedness Paradoxical Negative Effects of Giftedness Gifted students are able to handle the general education curriculum with ease—putting in minimum effort while still earning high grades. The long-term effect of being able to excel without working hard is a lack of work habits. Their “developmentally advanced” status is lost in the long run without hard work.  Level of Education & Intelligence Level of Educatio Intelligen n ce Social Class (environmental factor) Heredity, environmen t, & IQ  Assigned Readings Textbook Sections 8.1-8.4 & 8.9 Supplementary readings posted on D2L – “Deductive Reasoning & Decision Making” – The introduction (the first two pages) of “Confirmation bias: why psychiatrist stick to wrong preliminary diagnoses.”