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Richard J. Haier’s Followers (38)
Richard J. Haier
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“The heritability estimate of general intelligence was 26% at age 5, 39% at age 7, 54% at age 10, 64% at age 12, and starting at age 18 the estimate grew to over 80%.”
― The Neuroscience of Intelligence
― The Neuroscience of Intelligence
“1.10 Four Kinds of Predictive Validity for Intelligence Tests
1.10.3. Everyday Life
The importance of general intelligence in everyday life often is not obvious but it is profound. As Professor Earl Hunt has pointed out, if you are a college-educated person, it is highly likely that most of your friends and acquaintances are as well. When is the last time you invited someone to your home for dinner that was not college-educated? Professor Hunt calls this cognitive segregation and it is powerful in fostering the erroneous belief that everyone has a similar capacity or potential for reasoning about daily problems and issues. Most people with high g cannot easily imagine what daily life is like for a person with low g.
[...]
Consider some statistics comparing low and high IQ groups (low = 75–90; high = 110–125) on relative risk of several life events. For example, the odds of being a high school dropout are 133 times more likely if you’re in the low group. People in the low group are 10 times more at risk for being a chronic welfare recipient. The risk is 7.5 times greater in the low group for incarceration, and 6.2 times more for living in poverty. Unemployment and even divorce are a bit more likely in the low group. IQ even predicts traffic accidents. In the high IQ group, the death rate from traffic accidents is about 51 per 10,000 drivers, but in the low IQ group, this almost triples to about 147. This may be telling us that people with lower IQ, on average, have a poorer ability to assess risk and may take more chances when driving or performing other activities (Gottfredson, 2002; 2003b).”
― The Neuroscience of Intelligence
1.10.3. Everyday Life
The importance of general intelligence in everyday life often is not obvious but it is profound. As Professor Earl Hunt has pointed out, if you are a college-educated person, it is highly likely that most of your friends and acquaintances are as well. When is the last time you invited someone to your home for dinner that was not college-educated? Professor Hunt calls this cognitive segregation and it is powerful in fostering the erroneous belief that everyone has a similar capacity or potential for reasoning about daily problems and issues. Most people with high g cannot easily imagine what daily life is like for a person with low g.
[...]
Consider some statistics comparing low and high IQ groups (low = 75–90; high = 110–125) on relative risk of several life events. For example, the odds of being a high school dropout are 133 times more likely if you’re in the low group. People in the low group are 10 times more at risk for being a chronic welfare recipient. The risk is 7.5 times greater in the low group for incarceration, and 6.2 times more for living in poverty. Unemployment and even divorce are a bit more likely in the low group. IQ even predicts traffic accidents. In the high IQ group, the death rate from traffic accidents is about 51 per 10,000 drivers, but in the low IQ group, this almost triples to about 147. This may be telling us that people with lower IQ, on average, have a poorer ability to assess risk and may take more chances when driving or performing other activities (Gottfredson, 2002; 2003b).”
― The Neuroscience of Intelligence
“1.11 Why Do Myths About Intelligence Definitions and Measurement Persist?
Given all this strong empirical evidence that intelligence test scores are meaningful, why does the myth persist that scores have little if any validity? Here is an informative example. From time to time, a college admissions representative will assert that in their institution they find no relationship between grade point average (GPA) and SAT scores. Such observations are virtually always based on a lack of understanding of a basic statistical principle regarding the correlation between two variables. To calculate a correlation between any two variables, there must be a wide range of scores for each variable. At a place like MIT, for example, most students fall in a narrow range of high SAT scores. This is a classic problem of restriction of range. There is little variance among the students, so in this case, the relationship between GPA and SAT scores will not be very strong. Sampling from just the high end or just the low end or just the middle of a distribution restricts range and results in spuriously low or zero correlations. Restriction of range actually accounts for many findings about what intelligence test scores “fail” to predict.”
― The Neuroscience of Intelligence
Given all this strong empirical evidence that intelligence test scores are meaningful, why does the myth persist that scores have little if any validity? Here is an informative example. From time to time, a college admissions representative will assert that in their institution they find no relationship between grade point average (GPA) and SAT scores. Such observations are virtually always based on a lack of understanding of a basic statistical principle regarding the correlation between two variables. To calculate a correlation between any two variables, there must be a wide range of scores for each variable. At a place like MIT, for example, most students fall in a narrow range of high SAT scores. This is a classic problem of restriction of range. There is little variance among the students, so in this case, the relationship between GPA and SAT scores will not be very strong. Sampling from just the high end or just the low end or just the middle of a distribution restricts range and results in spuriously low or zero correlations. Restriction of range actually accounts for many findings about what intelligence test scores “fail” to predict.”
― The Neuroscience of Intelligence
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