The g factor, the science of mental ability – Arthur R. Jensen, ebook download pdf free

 

This is a very interesting book. Without a doubt the best about intelligence that i hav read so far. I definitely recommend reading it if one is interested in psychometrics. It can serve as a long, good, but a bit dated introduction to the subject. For shorter introductions, probably Gottfredson’s why g matters is better.

 

 

Quotes and comments below. Red text = quotes.

——-

 

Galton had no tests for obtaining direct measurements of cognitive ability.

Yet he tried to estimate the mean levels of mental capacity possessed by different

racial and national groups on his interval scale of the normal curve. His esti­

mates—many would say guesses—were based on his observations of people of

different races encountered on his extensive travels in Europe and Africa, on

anecdotal reports of other travelers, on the number and quality of the inventions

and intellectual accomplishments of different racial groups, and on the percent­

age of eminent men in each group, culled from biographical sources. He ven­

tured that the level of ability among the ancient Athenian Greeks averaged “ two

grades” higher than that of the average Englishmen of his own day. (Two grades

on Galton’s scale is equivalent to 20.9 IQ points.) Obviously, there is no pos­

sibility of ever determining if Galton’s estimate was anywhere near correct. He

also estimated that African Negroes averaged “ at least two grades” (i.e., 1.39a,

or 20.9 IQ points) below the English average. This estimate appears remarkably

close to the results for phenotypic ability assessed by culture-reduced IQ tests.

Studies in sub-Saharan Africa indicate an average difference (on culture-reduced
nonverbal tests of reasoning) equivalent to 1.43a, or 21.5 IQ points between

blacks and whites.8 U.S. data from the Armed Forces Qualification Test (AFQT),

obtained in 1980 on large representative samples of black and white youths,

show an average difference of 1.36a (equivalent to 20.4 IQ points)—not far

from Galton’s estimate (1.39a, or 20.9 IQ points).9 But intuition and informed

guesses, though valuable in generating hypotheses, are never acceptable as ev­

idence in scientific research. Present-day scientists, therefore, properly dismiss

Galton’s opinions on race. Except as hypotheses, their interest is now purely

biographical and historical.

 

yes there is. first, one can check the historical record to look for dysgenic effects. if the british are less smart than the ancient greeks, there wud probably hav been som dysgenic effects somwher in history. still, this is not a good method, since the population groups are somwhat different.

 

second, soon we will know the genes that cause different levels of intelligence. we can then analyze the remains of ancient greeks to see which genes they had. this shud giv a pretty good estimate, altho not perfect since, that 1) new mutations hav com by since then, 2) som gene variants hav perhaps disappeared, 3) the difficulty of getting a representativ sample of ancient greeks to test from, 4) the problems with getting good enuf quality DNA to run tests on. still, i dont think these are impossible to overcom, and i predict that som decent estimate can be made.

 

 

A General Factor Is Not Inevitable. Factor analysis is not by its nature

bound to produce a general factor regardless of the nature of the correlation

matrix that is analyzed. A general factor emerges from a hierarchical factor

analysis if, and only if, a general factor is truly latent in the particular correlation

matrix. A general factor derived from a hierarchical analysis should be based

on a matrix of positive correlations that has at least three latent roots (eigen­

values) greater than 1.

For proof that a general factor is not inevitable, one need only turn to studies

of personality. The myriad of inventories that measure various personality traits

have been subjected to every type of factor analysis, yet no general factor has

ever emerged in the personality domain. There are, however, a great many first-

order group factors and several clearly identified second-order group factors, or

“ superfactors” (e.g., introversion-extraversion, neuroticism, and psychoticism),

but no general factor. In the abilities domain, on the other hand, a general factor,

g, always emerges, provided the number and variety of mental tests are sufficient

to allow a proper factor analysis. The domain of body measurements (including

every externally measurable feature of anatomy) when factor analyzed also

shows a large general factor (besides several small group factors). Similarly, the

correlations among various measures of athletic ability show a substantial gen­

eral factor.

 

 

Jensen was wrong about this, altho the significance of that is disputed afaict. see:

How important is the General Factor of Personality? A General Critique (William Revelle and Joshua Wilt), PDF

 

 

In jobs where assurance of competence is absolutely critical, however, such

as airline pilots and nuclear reactor operators, government agencies seem to have

recognized that specific skills, no matter how well trained, though essential for

job performance, are risky if they are not accompanied by a fairly high level of

g. For example, the TVA, a leader in the selection and training of reactor op­

erators, concluded that results of tests of mechanical aptitude and specific job

knowledge were inadequate for predicting an operator’s actual performance on

the job. A TVA task force on the selection and training of reactor operators

stated: “ intelligence will be stressed as one of the most important characteristics

of superior reactor operators.. . . intelligence distinguishes those who have

merely memorized a series of discrete manual operations from those who can

think through a problem and conceptualize solutions based on a fundamental

understanding of possible contingencies.” 161 This reminds one of Carl Bereiter’s

clever definition of “ intelligence” as “ what you use when you don’t know

what to do.”

 

funny and true

 

 

The causal underpinnings of mental development take place at the neurolog­

ical level even in the absence of any specific environmental inputs such as those

that could possibly explain mental growth in something like figure copying in

terms of transfer from prior learning. The well-known “ Case of Isabel” is a

classic example.181 From birth to age six, Isabel was totally confined to a dimly

lighted attic room, where she lived alone with her deaf-mute mother, who was

her only social contact. Except for food, shelter, and the presence of her mother,

Isabel was reared in what amounted to a totally deprived environment. There

were no toys, picture books, or gadgets of any kind for her to play with. When

found by the authorities, at age six, Isabel was tested and found to have a mental

age of one year and seven months and an IQ of about 30, which is barely at

the imbecile level. In many ways she behaved like a very young child; she had

no speech and made only croaking sounds. When handed toys or other unfa­

miliar objects, she would immediately put them in her mouth, as infants nor­

mally do. Yet as soon as she was exposed to educational experiences she

acquired speech, vocabulary, and syntax at an astonishing rate and gained six

years of tested mental age within just two years. By the age of eight, she had

come up to a mental age of eight, and her level of achievement in school was

on a par with her age-mates. This means that her rate of mental development—

gaining six years of mental age in only two years—was three times faster than

that of the average child. As she approached the age of eight, however, her

mental development and scholastic performance drastically slowed down and

proceeded thereafter at the rate of an average child. She graduated from high

school as an average student.

 

What all this means to the g controversy is that the neurological basis of

information processing continued developing autonomously throughout the six

years of Isabel’s environmental deprivation, so that as soon as she was exposed

to a normal environment she was able to learn those things for which she was

developmentally “ ready” at an extraordinarily fast rate, far beyond the rate for

typically reared children over the period of six years during which their mental

age normally increases from two to eight years. But the fast rate of manifest

mental development slowed down to an average rate at the point where the level

of mental development caught up with the level of neurological development.

Clearly, the rate of mental development during childhood is not just the result

of accumulating various learned skills that transfer to the acquisition of new

skills, but is largely based on the maturation of neural structures.

 

this reminds me of the person who suggested that we delay teaching math in schools for the same reason. it is simply more time-effective, and time is costly, both for the child who has limited freedom in the time spent in school, and for soceity becus that time cud hav been spent on teaching somthing else, or not spent at all and thus saved money on teachers.

 

the idea is that som math subjects takes very long to teach, say, 8 year olds, but can rapidly to taught to 12 year olds. so, using som invented numbers, the idea is that instead of spending 10 hours teaching long division to 8 year olds, we cud spend 2 hours teaching long division to 12 year olds, thus saving 8 eights that can be either used on somthing else that can be taught easily to 8 year olds, or simply freeing up the time for non-teaching activities.

 

see: www.inference.phy.cam.ac.uk/sanjoy/benezet/ for the original papers

 

 

Perhaps the most problematic test of overlapping neural elements posited by

the sampling theory would be to find two (or more) abilities, say, A and B, that

are highly correlated in the general population, and then find some individuals

in whom ability A is severely impaired without there being any impairment of

ability B. For example, looking back at Figure 5.2, which illustrates sampling

theory, we see a large area of overlap between the elements in Test A and the

elements in Test B. But if many of the elements in A are eliminated, some of

its elements that are shared with the correlated Test B will also be eliminated,

and so performance on Test B (and also on Test C in this diagram) will be

diminished accordingly. Yet it has been noted that there are cases of extreme

impairment in a particular ability due to brain damage, or sensory deprivation

due to blindness or deafness, or a failure in development of a certain ability due

to certain chromosomal anomalies, without any sign of a corresponding deficit

in other highly correlated abilities.22 On this point, behavioral geneticists Will-

erman and Bailey comment: “ Correlations between phenotypically different

mental tests may arise, not because of any causal connection among the mental

elements required for correct solutions or because of the physical sharing of

neural tissue, but because each test in part requires the same ‘qualities’ of brain

for successful performance. For example, the efficiency of neural conduction or

the extent of neuronal arborization may be correlated in different parts of the

brain because of a similar epigenetic matrix, not because of concurrent func­

tional overlap.” 22 A simple analogy to this would be two independent electric

motors (analogous to specific brain functions) that perform different functions

both running off the same battery (analogous to g). As the battery runs down,

both motors slow down at the same rate in performing their functions, which

are thus perfectly correlated although the motors themselves have no parts in

common. But a malfunction of one machine would have no effect on the other

machine, although a sampling theory would have predicted impaired perform­

ance for both machines.

 

i know its only an analogy, but whether ther ar one or two motors tapping from one battery might hav an effect on their speed. that depends on the setup, i think.

 

 

Gc is most highly loaded in tests based on scholastic knowledge and cultural

content where the relation-eduction demands of the items are fairly simple. Here

are two examples of verbal analogy problems, both of about equal difficulty in

terms of percentage of correct responses in the English-speaking general pop­

ulation, but the first is more highly loaded on G f and the second is more highly

loaded on Gc.

 

1. Temperature is to cold as Height is to

(a) hot (b) inches (c) size (d) tall (e) weight

2. Bizet is to Carmen as Verdi is to

(a) Aida (b) Elektra (c) Lakme (d) Manon (e) Tosca

 

first one, i wanted to answer <small>, since <cold> is on the bottum of the scale of temperature, so i wanted somthing that was on the bottom of the scale of height. but ther is no such option, but tall is also on the scale of height, just as cold is on the scale of temperature. with no other better option, i went with (d), which was correct.

 

second one, however, made no sense to me. i did look for patterns in spelling, vowels, length, etc., found nothing. i then googled it. its composers and their operas.

en.wikipedia.org/wiki/Georges_Bizet

en.wikipedia.org/wiki/Carmen

en.wikipedia.org/wiki/Giuseppe_Verdi

en.wikipedia.org/wiki/Aida

 

 

Another blood variable of interest is the amount of uric acid in the blood

(serum urate level). Many studies have shown it to have only a slight positive

correlation with IQ. But it is considerably more correlated with measures of

ambition and achievement. Uric acid, which has a chemical structure similar to

caffeine, seems to act as a brain stimulant, and its stimulating effect over the

course of the individual’s life span results in more notable achievements than

are seen in persons of comparable IQ, social and cultural background, and gen­

eral life-style, but who have a lower serum urate level. High school students

with elevated serum urate levels, for example, obtain higher grades than their

IQ-matched peers with an average or below-average serum urate level, and,

amusingly, one study found a positive correlation between university professors’

serum urate levels and their publication rates. The undesirable aspect of high

serum urate level is that it predisposes to gout. In fact, that is how the association

was originally discovered. The English scientist Havelock Ellis, in studying the

lives and accomplishments of the most famous Britishers, discovered that they

had a much higher incidence of gout than occurs in the general population.

Asthma and other allergies have a much-higher-than-average frequency in

children with higher IQs (over 130), particularly those who are mathematically

gifted, and this is an intrinsic relationship. The intellectually gifted show some

15 to 20 percent more allergies than their siblings and parents. The gifted are

also more apt to be left-handed, as are the mentally retarded; the reason seems

to be that the IQ variance of left-handed persons is slightly greater than that of

the right-handed, hence more of the left-handed are found in the lower and upper

extremes of the normal distribution of IQ.

 

Then there are also a number of odd and less-well-established physical cor­

relates of IQ that have each shown up in only one or two studies, such as vital

capacity (i.e., the amount of air that can be expelled from the lungs), handgrip

strength, symmetrical facial features, light hair color, light eye color, above-

average basic metabolic rate (all these are positively correlated with IQ), and

being unable to taste the synthetic chemical phenylthiocarbamide (nontasters are

higher both in g and in spatial ability than tasters; the two types do not differ

in tests of clerical speed and accuracy). The correlations are small and it is not

yet known whether any of them are within-family correlations. Therefore, no

causal connection with g has been established.

 

Finally, there is substantial evidence of a positive relation between g and

general health or physical well-being.[36] In a very large national sample of high

school students (about 10,000 of each sex) there was a correlation of +.381

between a forty-three-item health questionnaire and the composite score on a

large number of diverse mental tests, which is virtually a measure of g. By

comparison, the correlation between the health index and the students’ socio­

economic status (SES) was only +.222. Partialing out g leaves a very small

correlation ( + .076) between SES and health status. In contrast, the correlation

between health and g when SES is partialed out is +.326.

 

how very curius!

 

 

Certainly psychometric tests were never constructed with the intention of

measuring inbreeding depression. Yet they most certainly do. At least fourteen

studies of the effects of inbreeding on mental ability test scores—mostly IQ—

have been reported in the literature.132′ Without exception, all of the studies show

inbreeding depression both of IQ and of IQ-correlated variables such as scho­

lastic achievement. As predicted by genetic theory, the IQ variance of the inbred

is greater than that of the noninbred samples. Moreover, the degree to which

IQ is depressed is an increasing monotonic function of the coefficient of in-

breeding. The severest effects are seen in the offspring of first-degree incestuous

matings (e.g., father-daughter, brother-sister); the effect is much less for first-

cousin matings and still less for second-cousin matings. The degree of IQ de­

pression for first cousins is about half a standard deviation (seven or eight IQ

points).

 

In most of these studies, social class and other environmental factors are well

controlled. Studies in Muslim populations in the Middle East and India are

especially pertinent. Cousin marriages there are more prevalent in the higher

social classes, as a means of keeping wealth in family lines, so inbreeding and

high SES would tend to have opposite and canceling effects. The observed effect

of inbreeding depression on IQ in the studies conducted in these groups,

therefore, cannot be attributed to the environmental effects of SES that are often

claimed to explain IQ differences between socioeconomically advantaged and

disadvantaged groups.

 

These studies unquestionably show inbreeding depression for IQ and other

single measures of mental ability. The next question, then, concerns the extent

to which g itself is affected by inbreeding. Inbreeding depression could be

mainly manifested in factors other than g, possibly even in each test’s specificity.

To answer this question, we can apply the method of correlated vectors to in-

breeding data based on a suitable battery of diverse tests from which g can be

extracted in a hierarchical factor analysis. I performed these analyses1331 for the

several large samples of children born to first-and second-cousin matings in

Japan, for whom the effects of inbreeding were intensively studied by geneticists

William Schull and James Neel (1965). All of the inbred children and compa­

rable control groups of noninbred children were tested on the Japanese version

of the Wechsler Intelligence Scale for Children (WISC). The correlations among

the eleven subtests of the WISC were subjected to a hierarchical factor analysis,

separately for boys and girls, and for different age groups, and the overall av­

erage g loadings were obtained as the most reliable estimates of g for each

subtest. The analysis revealed the typical factor structure of the WISC—a large

g factor and two significant group factors: Verbal and Spatial (Performance).

(The Memory factor could not emerge because the Digit Span subtest was not

used.) Schull and Neel had determined an index of inbreeding depression on

each of the subtests. In each subject sample, the column vector of the eleven

subtests’ g loadings was correlated with the column vector of the subtests’ index

of inbreeding depression (ID). (Subtest reliabilities were partialed out of these

correlations.) The resulting rank-order correlation between subtests’ g loadings

and their degree of inbreeding depression was + .79 (p < .025). The correlation

of ID with the Verbal factor loadings (independent of g) was +.50 and with the

Spatial (or Performance) factor the correlation was —.46. (The latter two cor­

relations are nonsignificant, each with p < .05.) Although this negative corre­

lation of ID with the spatial factor (independent of g) falls short of significance,

the negative correlation was found in all four independent samples. Moreover,

it is consistent with the hypothesis that spatial visualization ability is affected

by an X-linked recessive allele.34 Therefore, it is probably not a fluke.

 

A more recent study1351 of inbreeding depression, performed in India, was

based entirely on the male offspring of first-cousin parents and a control group

of the male offspring of genetically unrelated parents. Because no children of

second-cousin marriages were included, the degree of inbreeding depression was

considerably greater than in the previous study, which included offspring of

second-cousin marriages. The average inbreeding effect on the WISC-R Full

Scale IQ was about ten points, or about two-third of a standard deviation.1361

The inbreeding index was reported for the ten subtests of the WISC-R used in

this study. To apply the method of correlated vectors, however, the correlations

among the subtests for this sample are needed to calculate their g loadings.

Because these correlations were not reported, I have used the g loadings obtained

from a hierarchical factor analysis of the 1,868 white subjects in the WISC-R

standardization sample.1371 The column vector of these g loadings and the column

vector of the ID index have a rank-order correlation (with the tests’ reliability

coefficients partialed out) of +.83 (p < .01), which is only slightly larger than

the corresponding correlation between the g and ID vectors in the Japanese

study.

 

In sum, then, the g factor significantly predicts the degree to which perform­

ance on various mental tests is affected by inbreeding depression, a theoretically

predictable effect for traits that manifest genetic dominance. The larger a test’s

g loading, the greater is the depression of the test scores of the inbred offspring

of consanguineous parents, as compared with the scores of noninbred persons.

The evidence in these studies of inbreeding rules out environmental variables

as contributing to the observed depression of test scores. Environmental differ­

ences were controlled statistically, or by matching the inbred and noninbred

groups on relevant indices of environmental advantage.

 

pretty large effects. the footnote with the 14 studies mentioned is:

 

Adams & Neel, 1967; Afzal, 1988; Afzal & Sinha, 1984; Agrawal et al., 1984;

Badaruddoza & Afzil, 1993; Bashi, 1977; Book, 1957; Carter, 1967; Cohen et al., 1963;

Inbaraj & Rao, 1978; Neel, et al., 1970; Schull & Neel, 1965; Seemanova, 1971; Slatis

& Hoene, 1961.

 

 

Semantic Verification Test. The SVT uses the binary response console (Fig­

ure 8.3) and a computer display screen. Following the preparatory “ beep,” a

simple statement appears on the screen. The statement involves the relative

positions of the three letters A, B, C as they may appear (equally spaced) in a

horizontal array. Each trial uses one of the six possible permutations of these

three letters chosen at random. The statement appears on the screen for three

seconds, allowing more than enough time for the subject to read it. There are

fourteen possible statements of the following types: “ A after B,” “ C before

A,” “ A between B and C,” “ B first,” “ B last,” “ C before A and B,” “ C

after B and A” ; and the negative form of each of these statements, for instance,

“ A not after B.” Following the three-second appearance of one of these state­

ments, the screen goes blank for one second and then one of the permutations

of the letters A B C appears. The subject responds by pressing either the TRUE

or FALSE button, depending on whether the positions of the letters does or does

not agree with the immediately previous statement.

 

Although the SVT is the most complex of the many ECTs that have been

tried in my lab, the average RT for university students is still less than 1 second.

The various “ problems” differ widely in difficulty, with average RTs ranging

from 650 msec to 1,400 msec. Negative statements take about 200 msec longer

than the corresponding positive statements. MT, on the other hand, is virtually

constant across conditions, indicating that it represents something other than

speed of information processing.

 

The overall median RT and RTSD as measured in the SVT each correlates

about —.50 with scores on the Raven’s Advanced Progressive Matrices given

without time limit. The average RT on the SVT also shows large differences

between Navy recruits and university students,1201 and between academically

gifted children and their less gifted siblings.1211 The fact that there is a within-

families correlation between RT and IQ indicates that these variables are intrin­

sically and functionally related.

 

One study20 reveals that the average processing time for each of the fourteen

types of SVT statements in university students predicts the difficulty level of

the statements (in terms of error responses) in children (third-graders) who were

given the SVT as a nonspeeded paper-and-pencil test. While the SVT is of such

trivial difficulty for college students that individual differences are much more

reliably reflected by RT rather than by errors, the SVT items are relatively

difficult for young children. Even when they take the SVT as a nonspeeded

paper-and-pencil test, young children make errors on about 20 percent of the

trials. (The few university students who made even a single error under these

conditions, given as a pretest, were screened out.) The fact that the rank order

of the children’s error rates on the various types of SVT statements closely

corresponds to the rank order of the college students’ average RTs on the same

statements indicates that item difficulty is related to speed of processing, even

when the test is nonspeeded.

 

It appears that if information exceeds a critical level of complexity for the in­

dividual, the individual’s speed of processing is too slow to handle the infor­

mation all at once; the system becomes overloaded and processing breaks

down, with resulting errors, even for nonspeeded tests on which subjects are

told to take all the time they need. There are some items in Raven’s Advanced

Matrices, for example, that the majority of college students cannot solve with

greater than chance success, even when given any amount of time, although the

problems do not call for the retrieval of any particular knowledge. As already

noted, the scores on such nonspeeded tests are correlated with the speed of in­

formation processing in simple ECTs that are easily performed by all subjects

in the study.

 

interesting test. the threshold hypothesis is also interesting for makers of IQ tests.

 

 

There are many other kinds of simple tasks that do not resemble the con­

tents of conventional psychometric tests but that have significant correlations

with IQ. Many studies have confirmed Spearman’s finding that pitch discrim­

ination is g-loaded, and other musical discriminations, in duration, timbre,

rhythmic pattern, pitch interval, and harmony, are correlated with IQ, indepen­

dently of musical training.28 The strength of certain optical illusions is also

significantly related to IQ.1291 Surprisingly, higher-IQ subjects experience cer­

tain illusions more strongly than subjects with lower IQ, probably because

seeing the illusion implies a greater amount of mental transformation of the

stimulus, and tasks that involve transformation of information (e.g., backward

digit span) are typically more g loaded than tasks involving less transforma­

tion of the input (e.g., forward digit span). The positive correlation between

IQ and susceptibility to illusions is consistent with the fact that susceptibility

to optical illusions also increases with age, from childhood to maturity, and

then decreases in old age—the same trajectory we see for raw-score perform­

ance on IQ tests and for speed and intraindividual consistency of RT in ECTs.

The speed and consistency of information processing generally show an in­

verted U curve across the life span.

 

interesting.

 

 

Jensen mentions the en.wikipedia.org/wiki/Yerkes-Dodson_law

interesting. i link to Wikipedia since i think its explanation of the law is better than Jensens, who just briefly mentions it.

 

 

[…Localized damage to the brain

areas that normally subserve one of these group factors can leave the person

severely impaired in the expression of the abilities loaded on the group factor,

but with little or no impairment of abilities that are loaded on other group factors

or on g.]

 

A classic example of this is females who are born with a chromosomal anom­

aly known as Turner’s syndrome.1701 Instead of having the two normal female

sex chromosomes (designated XX), they lack one X chromosome (hence are

designated XO). Provided no spatial visualization tests are included in the IQ

battery, the IQs of these women (and presumably their levels of g) are normally

distributed and virtually indistinguishable from that of the general population.

Yet their performance on all tests that are highly loaded on the spatial-

visualization factor is extremely low, typically borderline retarded, even in

Turner’s syndrome women with verbal IQs above 130. It is as if their level of

g is almost totally unreflected in their level of performance on spatial tasks.

 

It is much harder to imagine the behavior of persons who are especially

deficient in all abilities involving g and all of the major group factors, but have

only one group factor that remains intact. In our everyday experience, persons

who are highly verbal, fluent, articulate, and use a highly varied vocabulary,

speaking with perfect syntax and appropriate expression, are judged to be of at

least average or probably superior IQ. But there is a rare and, until recently,

little-known genetic anomaly, Williams syndrome,1711 in which the above-listed

characteristics of high verbal ability are present in persons who are otherwise

severely mentally deficient, with IQs averaging about 50. In most ways, Wil­

liams syndrome persons appear to behave with no more general capability of

getting along in the world than most other persons with similarly low IQs. As

adults, they display only the most rudimentary scholastic skills and must live

under supervision. Only their spoken verbal ability has been spared by this

genetic defect. But their verbal ability appears to be “ hollow” with respect to

g. They speak in complete, often complex, sentences, with good syntax, and

even use unusual words appropriately. (They do surprisingly well on the Pea­

body Picture Vocabulary Test.) In response to a series of pictures, they can tell

a connected and fully elaborated story, accompanied by appropriate, if somewhat

exaggerated, emotional expression. Yet they have exceedingly little ability to

reason, or to explain or summarize the meaning of what they say. On most

spatial ability tests they generally perform on a par with Down syndrome persons

of comparable IQ, but they also differ markedly from Down persons in peculiar

ways. Williams syndrome subjects are more handicapped than IQ-matched

Down subjects in figure copying and block designs.

 

Comparing Turner’s syndrome with Williams syndrome obviously suggests

the generalization that a severe deficiency of one group factor in the presence

of an average level of g is far less a handicap than an intact group factor in the

presence of a very low level of g.

 

never heard of Williams syndrome befor.

 

en.wikipedia.org/wiki/Williams_syndrome

 

 

The correlation of IQ with grades and achievement test scores is highest (.60

to .70) in elementary school, which includes virtually the entire child population

and hence the full range of mental ability. At each more advanced educational

level, more and more pupils from the lower end of the IQ distribution drop out,

thereby restricting the range of IQs. The average validity coefficients decrease

accordingly: high school (.50 to .60), college (.40 to .50), graduate school (.30

to .40). All of these are quite high, as validity coefficients go, but they permit

far less than accurate prediction of a specific individual. (The standard error of

estimate is quite large for validity coefficients in this range.)

 

interesting. one thing that i hav been thinking about is that my GPA thruout my life has always been a bit abov average, but not close to the top. given that the intelligence requirement for each new step on the way thru the school system increases, one wud hav expected a drop in GPA, but no such thing happened. in fact, its the other way around. my GPA is the danish elementary school is 9.3 (9th grade) the average is ~8.1. this includes grades from non-intellectual subjects such as the ‘subject’ of having a nice hand-writing (yes seriusly). in 10th grade my average was 8.7, and the average is ~6.6. the max is 13 in all cases, altho normally grades abov 11 wer not given.

 

in gymnasiet (high school equiv.ish), my GPA was 7.8 and the average is 7.0. the slightly slower grades is becus the system was changed from a 13-step to a 7-step scale. and for comparison reasons, one can note that i went to HTX which has lower grades. the percentile level is 65th.

 

my university grades befor dropping out of filosofy were rather good, lots of 10’s, but i dont know the average, so cant compare. i suspect they were abov average again.

 

 

Unless an individual has made the transition from word reading to reading

comprehension of sentences and paragraphs, reading is neither pleasurable nor

practically useful. Few adults with an IQ of eighty (the tenth percentile of the

overall population norm) ever make the transition from word reading skill to

reading comprehension. The problem of adult illiteracy (defined as less than a

fourth-grade level of reading comprehension) in a society that provides an ele­

mentary school education to virtually its entire population is therefore largely a

problem of the lower segment of the population distribution of g. In the vast

majority of people with low reading comprehension, the problem is not word

reading per se, but lack of comprehension. These individuals score about the

same on tests of reading comprehension even if the test paragraphs are read

aloud to them by the examiner. In other words, individual differences in oral

comprehension and in reading comprehension are highly correlated.12’1

 

80.. but the american black average is only about 85. is it really true that ~37% of them ar too dull to learn to read properly? compared with ~10% of whites.

 

 

Virtually every type of work calls for behavior that is guided by cognitive

processes. As all such processes reflect g to some extent, work proficiency is g

loaded. The degree depends on the level of novelty and cognitive complexity

the job demands. No job is so simple as to be totally without a cognitive com­

ponent. Several decades of empirical studies have shown thousands of correla­

tions of various mental tests with work proficiency. One of the most important

conclusions that can be drawn from all this research is that mental ability tests

in general have a higher success rate in predicting job performance than any

other variables that have been researched in this context, including (in descend­

ing order of average predictive validity) skill testing, reference checks, class

rank or grade-point average, experience, interview, education, and interest meas­

ures.1221 In recent years, one personality constellation, characterized as “ consci­

entiousness,” has emerged near the top of the list (just after general mental

ability) as a predictor of occupational success.

 

reminds me that i ought to look into this field of psychology. its called I/O psychology. som time back i talked with a phd (i think) on 4chan who studied that area. he said that if he had his way, he wud just rely on g alone to predict job performance, training etc. he recommended me a textbook, which i found on the internet.

 

Psychology Applied to Work, An Introduction to Industrial and Organizational Psychology – Paul M. Muchinsky

 

it seems decent.

 

 

A person cannot perform a job successfully without the specific knowledge

required by the job. Possibly such job knowledge could be acquired on the job

after a long period of trial-and-error learning. For all but the very simplest jobs,

however, trial-and-error learning is simply too costly, both in time and in errors.

Job training inculcates the basic knowledge much more efficiently, provided that

later on-the-job experience further enhances the knowledge or skills acquired in

prior job training. Because knowledge and skill acquisition depend on learning,

and because the rate of learning is related to g, it is a reasonable hypothesis that

g should be an effective predictor of individuals’ relative success in any specific

training program.

 

The best studies for testing this hypothesis have been performed in the armed

forces. Many thousands of recruits have been selected for entering different

training programs for dozens of highly specialized jobs based on their perform­

ance on a variety of mental tests. As the amount of time for training is limited,

efficiency dictates assigning military personnel to the various training schools

so as to maximize the number who can complete the training successfully and

minimize the number who fail in any given specialized school. When a failed

trainee must be rerouted to a different training school better suited to his apti­

tude, it wastes time and money. Because the various schools make quite differing

demands on cognitive abilities, the armed services employ psychometric re­

searchers to develop and validate tests to best predict an individual’s probability

of success in one or another of the various specialized schools.

 

 

one is tempted to say ”common sense”, but apparently, only the military dares to do such things.

 

 

A rough analogy may help to make the essential point. Suppose that for some

reason it was impossible to measure persons’ heights directly in the usual way,

with a measuring stick. However, we still could accurately measure the length

of the shadow cast by each person when the person is standing outdoors in the

sunlight. Provided everyone’s shadow is measured at the same time of day, at

the same day of the year, and at the same latitude on the earth’s surface, the

shadow measurements would show exactly the same correlations with persons’

weight, shoe size, suit or dress size, as if we had measured everyone directly

with a yardstick; and the shadow measurements could be used to predict per­

fectly whether or not a given person had to stoop when walking through a door

that is only 5 ‘/2 -feet high. However, if one group of persons’ shadows were

measured at 9:00 a .m . and another group’s at 10:00 a .m ., the pooled measure­

ments would show a much smaller correlation with weight and other factors

than if they were all measured at the same time, date, and place, and the meas­

urements would have poor validity for predicting which persons could walk

through a 5 ‘/2 -foot door without stooping. We would say, correctly, that these

measurements are biased. In order to make them usefully accurate as predictors

of a person’s weight and so forth, we would have to know the time the person’s

shadow was measured and could then add or subtract a value that would adjust

the measurement so as to make it commensurate with measurements obtained

at some other specific time, date, and location. This procedure would permit the

standardized shadow measurements of height, which in principle would be as

good as the measurements obtained directly with a measuring stick.

 

Standardized IQs are somewhat analogous to the standardized shadow meas­

urements of height, while the raw scores on IQ tests are more analogous to the

raw measurements of the shadows themselves. If we naively remain unaware

that the shadow measurements vary with the time of day, the day of the year,

and the degrees of latitude, our raw measurements would prove practically

worthless for comparing individuals or groups tested at different times, dates,

or places. Correlations and predictions could be accurate only within each unique

group of persons whose shadows were measured at the same time, date, and

place. Since psychologists do not yet have the equivalent of a yardstick for

measuring mental ability directly, their vehicles of mental measurement—IQ

scores—are necessarily “ shadow” measurements, as in our height analogy, al­

beit with amply demonstrated practical predictive validity and construct validity

within certain temporal and cultural limits.

 

 

interesting. however, biologically based tests shud allow for absolut measurement, say tests based on RT in ECTs, or tests based on the amount of mylianation in the brain, or brain ph levels, brain size via brain imaging scans if we can make them better measurements of g, etc.

 

 

Many possible factors determine whether a person passes or fails a particular

test item. Does the person understand the item at all (e.g., “What is the sum of

all the latent roots of a 7 X 7 R matrix?” )? Has the person acquired the specific

knowledge called for by the item (e.g., “Who wrote Faust?”), or perhaps has

he acquired it in the past and has since forgotten it? Did the person really know

the answer, but just couldn’t recall it at the moment of being tested? Does the

item call for a cognitive skill the person either never acquired or has forgotten

through disuse (e.g., “ How much of a whole apple is two-thirds of one-half of

the apple?” )? Does the person understand the problem and know how to solve

it, but is unable to do it within the allotted time limit (e.g., substituting the

corresponding letter of the alphabet for each of the numbers from one to twenty-

six listed in a random order in one minute)? Or even when there is a liberal

time limit does the person give up on the item or just guess at the answer

prematurely, perhaps because the item looks too complicated at first glance (e.g.,

“ If it takes six garden hoses, all running for three hours and thirty minutes to

fill a tank, how many additional hoses would be needed to fill the tank in thirty

minutes?” )?

 

1) dunno

2) Goethe

3) 2/3*1/2=4/6*3/6=12/36=1/3

4) #hose*time=tank size

6*3.5=21

21 is the size of the tank

21=0.5*#hose, solve #hose

42=#hose

42-6=36

36 more hoses

 

 

The only study I have found that investigated whether there has been a secular

change (over thirty years) in the heritability of g-loaded test scores concluded

that “ the results revealed no unambiguous evidence for secular trends in the

heritability of intelligence test scores.” 1351 However, the heritability coefficients

(based on twenty-two same-age cohort samples of MZ and DZ male twins born

in Norway between 1930 and 1960) showed some statistically reliable nonlinear

trends over the thirty-year period, as shown in Figure 10.2. The overall trend

line goes equally down-up-down-up with heritability coefficients ranging from

slightly above .80 to slightly below .40. The heritability coefficient was the same

for the cohort born in 1930 as for the cohort born in 1960 (for both, h2 = .80).

The authors offer only weak ad hoc speculations about possible causes of this

erratic fluctuation of h2 across 22 points in time.

 

the hole is the german occupation of norway. the data from the 30s make sense to me, the depression wud result in civil unrest and the changing up of society. after a period of such, heritabilities shud stabilize again, as seen in the after war period. i dont understand the 50s down swing in heritability.

 

so, i thought it might be somthing economic. i gathered GDP data, and looked at the data. nope, not true.

 

www.norges-bank.no/pages/77409/p1_c6.xlsx

 

data from 1901 to 2000 looks like this:

gdp norway 50s

 

doesnt fit with the GDP hypothesis at all, except for missing data in the war.

 

i dunno, perhaps www.newsinenglish.no/2010/06/16/the-50s-in-norway-werent-so-nifty/

 

the authors of the study that found the drop in heritability also dont know ”We are, however, quite at a loss in explaining the dip from about 1950 to 1954. Thus, we feel that the best strategy at present is to leave the issue of secular trends open. ”

On the question of secular trends in the heritability of intelligence scores A study of Norwegian twins

 

Head Start. The federal preschool intervention known as Head Start, which

has been in continual existence now since 1964, is undoubtedly the largest-

scale, though not the most intensive, educational intervention program ever un­

dertaken, with an annual expenditure over $2 billion. The program is aimed at

improving the health status and the learning and social skills of preschoolers

from poor backgrounds so they can begin regular school more on a par with

children from more privileged backgrounds. The intervention is typically short­

term, with various programs lasting anywhere from a few months to two years.

 

The general conclusion of the hundreds of studies based on Head Start data

is that the program has little, if any, effect on IQ or scholastic achievement that

endures beyond more than two to three years after exposure to Head Start. The

program does, however, have some potential health benefits, such as inoculations

of enrollees against common childhood diseases and improved nutrition (by

school-provided breakfast or lunch). The documented behavioral effects are less

retention-in-grade and lower dropout rates. The cause(s) of these effects are

uncertain. Because eligible children were not randomly enrolled in Head Start,

but were selected by parents and program administrators, these scholastic cor­

relates of Head Start are uninterpretable from a causal standpoint. Selection,

rather than direct causation by the educational intervention itself, could be the

explanation of Head Start’s beneficial outcomes.

 

crazy amount of money spent for som slight health benefits. perhaps ther is a cheaper way to get such benefits.

 

 

The Milwaukee Project. Aside from Head Start, this is the most highly

publicized of all intervention experiments. It was the most intensive and exten­

sive educational intervention ever conducted for which the final results have

been published.55 It was also the most costly single experiment in the history of

psychology and education—over $14 million. In terms of the highest peak of

IQ gains for the seventeen children in the treatment condition (before the gains

began to vanish), the cost was an estimated $23,000 per IQ point per child.

 

holy shit. even tho i think iv seen this figur befor (in The g Factor by Chris Brand).

 

Jensen also doesnt mention the end of the project, but Wikipedia does:

en.wikipedia.org/wiki/Milwaukee_Project

 

The Milwaukee Project’s claimed success was celebrated in the popular media and by famous psychologists. However, later in the project Rick Heber, the principal investigator, was discharged from the University of Wisconsin–Madison and convicted and imprisoned for large-scale abuse of federal funding for private gain. Two of Heber’s colleagues in the project were also convicted for similar abuses. The project’s results were not published in any refereed scientific journals, and Heber did not respond to requests from colleagues for raw data and technical details of the study. Consequently, even the existence of the project as described by Heber has been called into question. Nevertheless, many college textbooks in psychology and education have uncritically reported the project’s results.[3][4]

 

this reminds me why open data is necessary in science.

 

 

[The Abecedarian Early Intervention Project.]

Both the T and C groups (each with about fifty subjects) were given age-

appropriate mental tests (Bayley, Stanford-Binet, McCarthy, WPPSI) at

six-month intervals from age six months to sixty months. The important com­

parisons here are the mean T-C differences at each testing. (Because the test

scores do not have the same factor composition across this wide age range,

the absolute scores of the T group alone are not as informative of the efficacy

of the intervention as are the mean T-C differences.) At every testing from six

months to five years of age, the T group outperformed the C group, and the

overall average T-C difference (103.3 — 95.5 = 7.8 IQ points) was highly

significant (p < .001). Peculiarly, however, the largest T-C differences (aver­

aging fifteen IQ points) occurred between eighteen and thirty-six months of

age and then declined during the last two years of intervention. At sixty

months, the average T-C difference was 7.5 IQ points. This decrease might

simply reflect the fact that with the children’s increasing age the tests become

increasingly more g-Ioaded. The tests used before two or three years of age

measure mainly perceptual-motor functions that have relatively little g satura­

tion. Only later does g becomes the predominant component of variance in

IQ. In follow-up studies at eight and twelve years of age, the T-C difference

on the WISC-R was about five IQ points,1571 a difference that has remained up

to age fifteen. At the last reported testing, the T-C difference was 4.6 IQ

points, or a difference of 0.35ct. Scholastic achievement test scores showed a

somewhat larger effect of the intervention up to age fifteen.1571 The interven­

tion effect on other criteria of the project’s success was demonstrated by the

decreased percentage of children who repeated at least one grade by age

twelve (T = 28 percent, C = 55 percent) and the percentage of children with

borderline or retarded intelligence (IQ < 85) (T = 12.8 percent, C = 44.2

percent).1561

 

Thus this five-year program of intensive intervention beginning in early in­

fancy increased IQ (at age fifteen years) by about five points. Judging from a

comparable gain in scholastic achievement, the effect had broad transfer, sug­

gesting that it probably raised the level of g to some extent. The finding that

the T subjects did better than the C subjects on a battery of Piaget’s tests of

conservation, which reflect important stages in mental development, is further

evidence. The Piagetian tests are not only very different in task demands from

anything in the conventional IQ tests used in the conventional assessments, but

are also highly g loaded.1571 The mean T-C difference on the Piagetian conser­

vation tests was equal to 0.33a (equivalent to five IQ points). Assuming that

the instructional materials in the intervention program did not closely resemble

Piaget’s tests, it is a warranted conclusion that the intervention appreciably

raised the Level of g.

 

im still skeptical as to the g effects. id like to see the data about them as adults, and a larger sample size.

 

again, Wikipedia has mor on the issue, both positiv and negativ:

en.wikipedia.org/wiki/Abecedarian_Early_Intervention_Project

Significant findings

Follow-up assessment of the participants involved in the project has been ongoing. So far, outcomes have been measured at ages 3, 4, 5, 6.5, 8, 12, 15, 21, and 30.[5] The areas covered were cognitive functioning, academic skills, educational attainment, employment, parenthood, and social adjustment. The significant findings of the experiment were as follows:[6][7]

Impact of child care/preschool on reading and math achievement, and cognitive ability, at age 21:

  • An increase of 1.8 grade levels in reading achievement
  • An increase of 1.3 grade levels in math achievement
  • A modest increase in Full-Scale IQ (4.4 points), and in Verbal IQ (4.2 points).

Impact of child care/preschool on life outcomes at age 21:

  • Completion of a half-year more of education
  • Much higher percentage enrolled in school at age 21 (42 percent vs. 20 percent)
  • Much higher percentage attended, or still attending, a 4-year college (36 percent vs. 14 percent)
  • Much higher percentage engaged in skilled jobs (47 percent vs. 27 percent)
  • Much lower percentage of teen-aged parents (26 percent vs. 45 percent)
  • Reduction of criminal activity

Statistically significant outcomes at age 30:

  • Four times more likely to have graduated from a four-year college (23 percent vs. 6 percent)
  • More likely to have been employed consistently over the previous two years (74 percent vs. 53 percent)
  • Five times less likely to have used public assistance in the previous seven years (4 percent vs. 20 percent)
  • Delayed becoming parents by average of almost two years

(Most recent information from Developmental Psychology, January 18, 2012, cited in uncnews.unc.edu, January 19, 2012)

The project concluded that high quality, educational child care from early infancy was therefore of utmost importance.

Other, less intensive programs, notably the Head Start Program, but also others, have not been as successful. It may be that they provided too little too late compared with the Abecedarian program.[4]

Criticisms

Some researchers have advised caution about the reported positive results of the project. Among other things, they have pointed out analytical discrepancies in published reports, including unexplained changes in sample sizes between different assessments and publications. It has also been noted that the intervention group’s reported 4.6 point advantage in mean IQ at age 15 was not statistically significant. Herman Spitz has noted that a mean IQ difference of similar magnitude to the final difference between the intervention and control groups was apparent already at age six months, indicating that “4 1/2 years of massive intervention ended with virtually no effect.” Spitz has suggested that the IQ difference between the intervention and control groups may have been present from the outset due to faulty randomization.[8]

 

not quite sure what to think. the sample sizes ar still kind small, and if Spitz is right in his criticism, the studies hav not shown much.

 

the reason that im skeptical to begin with is that the modern twin studies show, that shared environment, which is what these studies change to a large degree, has no effect on adult IQ.

 

in any case, if it requires so expensiv spendings to get slightly less dumb kids, its hard to justify as a public policy. at the very least, id like to see the calculation that finds that this has a net positiv benefit for society. it is possible, for instance, becus crime rates ar (supposedly) down, and job retention up which leads to mor taxes being paid, and so on.

 

 

Error distractors in multiple-choice answers are of interest as a method of

discovering bias. When a person fails to select the correct answer but instead

chooses one of the alternative erroneous responses (called “ distractors” ) offered

for an item in a multiple-choice test, the person’s incorrect choice is not random,

but is about as reliable as is the choice of the correct answer. In other words,

error responses, like correct responses, are not just a matter of chance, but reflect

certain information processes (or the failure of certain crucial steps in infor­

mation processing) that lead the person to choose not just any distractor, but a

particular one. Some types of errors result from a solution strategy that is more

naive or less sophisticated than other types of errors. For example, consider the

following test item:

 

If you mix a pint of water at 50° temperature with two pints of water at 80°

measured on the same thermometer, what will be the temperature of the mix­

ture? (a) 65°, (b) 70°, (c) 90°, (d) 130°, (e) Can’t say without knowing

whether the temperatures are Centigrade or Fahrenheit.

 

We see that the four distractors differ in the level of sophistication in mental

processing that would lead to their choice. The most naive distractor, for ex­

ample, is D, which is arrived at by simple addition of 50° and 80°. The answer

A at least shows that the subject realized the necessity for averaging the tem­

peratures. The answer 90° is the most sophisticated distractor, as it reveals that

the subject had a glimmer of the necessity for a weighted average (i.e., 50° +

8072 = 90°) but didn’t know how to go about calculating it. (The correct

answer, of course, is B, because the weighted average is [1 pint X 50° + 2

pints X 80°]/3 pints = 70°.) Preference for selecting different distractors changes

across age groups, with younger children being attracted to the less sophisticated

type of distractor, as indicated by comparing the percentage of children in dif­

ferent age groups that select each distractor. The kinds of errors made, therefore,

appear to reflect something about the children’s level of cognitive development.

 

interesting.

 

 

What is termed a cline results where groups overlap at their fuzzy boundaries

in some characteristic, with intermediate gradations of the phenotypic charac­

teristic, often making the classification of many individuals ambiguous or even

impossible, unless they are classified by some arbitrary rule that ignores biology.

The fact that there are intermediate gradations or blends between racial groups,

however, does not contradict the genetic and statistical concept of race. The

different colors of a rainbow do not consist of discrete bands but are a perfect

continuum, yet we readily distinguish different regions of this continuum as

blue, green, yellow, and red, and we effectively classify many things according

to these colors. The validity of such distinctions and of the categories based on

them obviously need not require that they form perfectly discrete Platonic cat­

egories.

 

while the rainbow analogy works to som extent, it is not that good. the reason is that with rainbows, all the colors (groups) ar on a continuum in such a way that ther isnt a blend between every two colors (groups). this is not how races work, as ther is always the possibility of a blend between any two groups, even odd groups such as amerindians and aboriginals.

 

 

Of the approximately 100,000 human polymorphic genes, about 50,000 are

functional in the brain and about 30,000 are unique to brain functions.[12] The

brain is by far the structurally and functionally most complex organ in the human

body and the greater part of this complexity resides in the neural structures of

the cerebral hemispheres, which, in humans, are much larger relative to total

brain size than in any other species. A general principle of neural organization

states that, within a given species, the size and complexity of a structure reflect

the behavioral importance of that structure. The reason, again, is that structure

and function have evolved conjointly as an integrated adaptive mechanism. But

as there are only some 50,000 genes involved in the brain’s development and

there are at least 200 billion neurons and trillions of synaptic connections in the

brain, it is clear that any single gene must influence some huge number of

neurons— not just any neurons selected at random, but complex systems of

neurons organized to serve special functions related to behavioral capacities.

 

It is extremely improbable that the evolution of racial differences since the

advent of Homo sapiens excluded allelic changes only in those 50,000 genes

that are involved with the brain.

 

the same point was made, altho less technically, in Hjernevask. ther is no good apriori reason to think that natural selection for som reason only worked on non-brain, non-behavioral genes. it simply makes no sense at all to suppose that.

 

 

Bear in mind that, from the standpoint of natural selection, a larger brain

size (and its corresponding larger head size) is in many ways decidedly disad­

vantageous. A large brain is metabolically very expensive, requiring a high-

calorie diet. Though the human brain is less than 2 percent of total body weight,

it accounts for some 20 percent of the body’s basal metabolic rate (BMR). In

other primates, the brain accounts for about 10 percent of the BMR, and for

most carnivores, less than 5 percent. A larger head also greatly increases the

difficulty of giving birth and incurs much greater risk of perinatal trauma or

even fetal death, which are much more frequent in humans than in any other

animal species. A larger head also puts a greater strain on the skeletal and

muscular support. Further, it increases the chances of being fatally hit by an

enemy’s club or missile. Despite such disadvantages of larger head size, the

human brain, in fact, evolved markedly in size, with its cortical layer accom­

modating to a relatively lesser increase in head size by becoming highly con­

voluted in the endocranial vault. In the evolution of the brain, the effects of

natural selection had to have reflected the net selective pressures that made an

increase in brain size disadvantageous versus those that were advantageous. The

advantages obviously outweighed the disadvantages to some degree or the in­

crease in hominid brain size would not have occurred.

 

this brain must hav been very useful for somthing. if som of this use has to do with non-social things, like environment, one wud expect to see different levels of ‘brain adaptation’ due to the relative differences in selection pressure in populations that evolved in different environments.

 

 

How then can the default hypothesis be tested empirically? It is tested exactly

as is any other scientific hypothesis; no hypothesis is regarded as scientific unless

predictions derived from it are capable of risking refutation by an empirical test.

Certain predictions can be made from the default hypothesis that are capable of

empirical test. I f the observed result differs significantly from the prediction, the

hypothesis is considered disproved, unless it can be shown that the tested pre­

diction was an incorrect deduction from the hypothesis, or that there are artifacts

in the data or methodological flaws in their analysis that could account for the

observed result. If the observed result does in fact accord with the prediction,

the hypothesis survives, although it cannot be said to be proven. This is because

it is logically impossible to prove the null hypothesis, which states that there is

no difference between the predicted and the observed result. If there is an al­

ternative hypothesis, it can also be tested against the same observed result.

 

For example, if we hypothesize that no tiger is living in the Sherwood Forest

and a hundred people searching the forest fail to find a tiger, we have not proved

the null hypothesis, because the searchers might have failed to look in the right

places. I f someone actually found a tiger in the forest, however, the hypothesis

is absolutely disproved. The alternative hypothesis is that a tiger does live in

the forest; finding a tiger clearly proves the hypothesis. The failure of searchers

to find the tiger decreases the probability of its existence, and the more search­

ing, the lower is the probability, but it can never prove the tiger’s nonexistence.

 

Similarly, the default hypothesis predicts certain outcomes under specified

conditions. If the observed outcome does not differ significantly from the pre­

dicted outcomes, the default hypothesis is upheld but not proved. If the predic­

tion differs significantly from the observed result, the hypothesis must be

rejected. Typically, it is modified to accord better with the existing evidence,

and then its modified predictions are empirically tested with new data. If it

survives numerous tests, it conventionally becomes a “ fact.” In this sense, for

example, it is a “ fact” that the earth revolves around the sun, and it is a “ fact”

that all present-day organisms have evolved from primitive forms.

 

meh, mediocre or bad filosofy of science.

 

 

 

 

the problem with this data is that the women were not don having children. the data is from women aged 34. since especially smart women (and so mor whites) hav children later than that age, their fertility estimates ar spuriusly low. see also the data in Intelligence: A Unifying Construct for the Social Sciences (Richard Lynn and Tatu Vanhanen, 2012).

 

 

Whites perform significantly better than blacks on the subtests called Com­

prehension, Block Design, Object Assembly, and Mazes. The latter three tests

are loaded on the spatial visualization factor of the WISC-R. Blacks perform

significantly better than whites on Arithmetic and Digit Span. Both of these tests

are loaded on the short-term memory factor of the WISC-R. (As the test of

arithmetic reasoning is given orally, the subject must remember the key elements

of the problem long enough to solve it.) It is noteworthy that Vocabulary is the

one test that shows zero W-B difference when g is removed. Along with Infor­

mation and Similarities, which even show a slight (but nonsignificant) advantage

for blacks, these are the subtests most often claimed to be culturally biased

against blacks. The same profile differences on the WISC-R were found in

another study|8lbl based on 270 whites and 270 blacks who were perfectly

matched on Full Scale IQ.

 

seems inconsistent with typical environment only theories.

 

 

 

0 Comments

Leave a Reply