From the book Hard Drive: Bill Gates and the Making of the Microsoft Empire:

Although Gates may not have known what he was going to do with his life during high school, he seemed confident that whatever he did would make him a lot of money. He made just such a prediction about his future on several occasions to other students and teachers at Lakeside. In the 11th grade, Gates told his friend Paul Carlson that he would be a millionaire by the time he was 30 years old.

“That is something that might sound like arrogance,” said Carlson. “Some might just say it to brag. Some might say it as if they had the measure of themselves. Bill was in that second category.”

A lot of people think that super genius billionaires like Bill Gates are motivated by their intellectual passion, and money is just a byproduct, but this seems to show that actually Bill Gates’s primary goal in life really was money.

Sometimes a cigar is just a cigar.

A lot of people who think they’re smart, eschew such blatant avarice as unseemly, preferring instead to pursue “higher” goals that bring meaning to their life.

However Bill Gates, whose IQ of 170 makes him one of the smartest people in the entire country, is smart enough to realize that whatever you want in life, chance are money can buy it for you.

There’s virtually nothing you could possibly want that money can’t help you buy.  You want love?  Money can buy you better looks and better clothes, and lavish parties to meet women, and romantic vacations when you find the girl of your dreams.

Want intellectual stimulation?  Money can buy you your own research lab, and the ability to hire thousands of people to participate in your studies

Want justice?  Money can help you buy media to expose the corrupt and charities to help the poor

Want to pass on your genes?  Money allows you to pay countless women to carry your child, and allows you to fund charities devoted to people who look like you.

Want more time?  Money allows you to retire early and hire staff to do all your cooking and cleaning

Want beauty and spiritual connection?  Money allows a home overlooking the ocean.

There’s a saying that money manages to signify intelligence in even the most unlikely of cases.  Someone could have an 8th grade education, and not even be able to string together a sentence, but if they have money, they will come across as shrewd.  Meanwhile someone can have a Nobel prize in physics, but if they are poor, people will say “if you’re so smart, why aren’t you rich?”

People intuitively understand that intelligence is ultimately the mental ability to adapt: To take whatever situation you’re in, and turn it around to your advantage.

And what’s more advantageous than money?

I’m now in my 30s, but when I was a teenager, I had a genetically superior Oriental friend, and when his mother found out I had a part time job, she was impressed I was making money.  Yet when my friend asked if he should get a partime job, his mother felt he was better off studying in school.

“Money now, mean nothing,” she said.  “Money later, mean… EVERYTHING!”

Bloomberg.com reports:

Black, Hispanic, and American Indian MBAs who got their degree six to eight years ago earned exactly as much as their white and Asian peers right after leaving school, according to a Bloomberg survey of 12,700 alumni at more than 100 business schools. In the survey, conducted as part of our annual ranking of full-time MBA programs, both groups said they made a median $105,000 when they graduated.

But by 2015, MBAs who were underrepresented minorities—meaning black, Hispanic, or American Indian—earned $150,000, while white and Asian MBAs made $172,000…The race pay gap is particularly wide at Harvard Business School, where black, Hispanic, and American Indian MBAs started out earning just $5,000 less than their white and Asian classmates. Six to eight years after graduating, that gap widened to $97,800.

This shows that affirmative action can level the playing field when it comes to elite credentials, but it doesn’t level the playing field when it comes to money.  This is likely either because Whites and Asians face less workplace discrimination and have more connections than non-Asian minorities, and/or it’s because IQ might predict income, perhaps even among people with equal degrees, and Whites and Asians have higher IQs.

Even though blacks are over 10% of graduates at elite schools, they are typically only 0.25% (sometimes 0.5%) of the 400 richest Americans, with Oprah being the ONLY multibillionaire black in North American history.

And yet Oprah attended only a very humble college in Tennessee.  She has no business training and once boasted that she didn’t even know how to read a balance sheet.

I could picture a lot of Ivy League minorities thinking “I’m smarter than Oprah.  I’m gona get a degree and be richer than her!”

What they don’t realize is that behind Oprah’s fuzzy persona, is a brain the size of a basketball, which allows her the intelligence to adapt in ways they can’t even imagine, let alone execute.

This might suggest “free market” capitalism is working somewhat like libertarians had hoped.  It’s not just about where you went to school, but a Darwinian contest where the biggest brained survive and prosper through real world adaptability, just like they did for 4 million years of human evolution.

Even  Barack Obama (who was the editor of the Harvard Law Review) was getting massacred in the polls by Hillary, until the big-brained Oprah stepped in and adapted for him, causing him to win the Democratic nomination and become President:

Commenter ruhkukah wants me to estimate the IQ of Chris Langan which got me addicted to listening to interviews with him on the internet.   There’s something so intimate about radio.  You can listen in the pitch black darkness of your bedroom against the freezing cold of a Canadian winter (yes we finally got snow).

I’m struck by how much Langan has in common with Oprah:

1)Both have super-human head size (Oprah 25.25” around; Langan 25.5” around)

2)Both learned to talk early

3) Both learned to read by age 3

4)Both skipped multiple years of primary school

5)Both are now  in their early 60s

6)Both got scholarships to mediocre colleges and dropped out (though Oprah went back to complete her degree after becoming rich and famous to set a good example)

7)Both don’t know for sure who their biological fathers are

8) Both were raised illegitimate in poverty by a mother who bounced from one bad relationship to another

9) Both were abused in childhood.

10)Both have weighed way over 200 lbs: Oprah from fat, Langan from muscle, which incidentally makes Oprah’s head even more impressive for her body size since such adjustments are made for only fat free body-weight

11)Both are obsessed with the idea of  God and speak of the universe as though it were a conscious entity, yet both embrace a universal theism and respect all faiths equally instead of being religious partisans.

12)Both seem to believe in controversial metaphysical ideas and are resented by the scientific establishment because of it.

Although I do think Oprah is EXTREMELY intelligent, I’m not suggesting she’s anywhere near the same IQ league as Langan, who has been called the smartest man in America, and is much more analytical about his metaphyisical ideas than Oprah is.

And yet it was Oprah who overcame the adversity to become the billionaire Queen of All Media while Langan became a bouncer earning $6000 a year.  If not IQ, what made the difference?  Oprah probably had certain talents, opportunities, personality traits, and support systems that Langan lacked.

Here’s an especially long interview with Langan.

In a previous posts I estimated Terance Tao’s IQ from SAT data.  In this post, I will estimate his reading IQ using historiometric data.

According to The New York Times Magazine, Terance Tao taught himself to read at age 2.  What IQ level does this equate to?  In order to answer this question, we need statistics about when kids learn to read.  The problem is, the distribution would not be normal, because most kids learn in school during first grade, so you get a pile up of kids all learning at one age.  But since Tao learned to read before entering school, it makes more sense to compare him to a sample of unschooled kids, both because they learned under similar circumstances, and because the distribution is presumably more normal when kids learn naturally.

In order to find such data, let’s turn to the unschooled movement, where kids are encouraged to learn on their own.  Scholar Peter Gray writes:

The stories sent to me by readers of this blog include 21 separate cases of children learning to read in which the age of first real reading (reading and understanding of novel passages of text) was mentioned. Of these, two learned at age 4, seven learned at age 5 or 6, six learned at age 7 or 8, five learned at age 9 or 10, and one learned at age 11.

Although this is not a random sample of American ability, it’s the only sample we’ve got, and the ages of unschooled reading seem to be:

4,4,5.5,5.5,5.5,5.5,5.5,5.5,5.5,7.5,7.5,7.5,7.5,7.5,7.5,9.5,9.5,9.5,9.5,9.5,11

The mean age is 7.14 (SD = 2.02).

Thus, Tao learning to read at age 2 makes him 2.48 standard deviations more precocious than average than the average American kid learning without the interference of schooling.  Thus, on the modern deviation IQ scale where scores are made to have a mean of 100 and a standard deviation of 15, Tao’s IQ is 138 (U.S. norms).

Although an IQ of 138 is extremely high (obtained by one in 177 Americans), it seems way too low for someone reading at age 2.  After all, a 2 year old who has acquired the mental skill of a 7.14-year-old, has developed at 357% the normal rate, implying a ratio IQ of 357.  I realize ratio IQs tend to be much higher than deviation IQs, especially at the extremes, but there’s no way in hell one in 177 kids have a ratio IQ of 357.  Obviously the deviation IQ of 138 is too low.

Age ratio IQs

A second approach is to assign ratio IQs to each of the 21 kids in the sample, and then see how man standard deviations above average Tao’s ratio IQ is.

In order to convert these ages into ratio IQs, we simply apply this formula:

Ratio IQ = [7.14/(age child learned to read outside school)][100]

Using this formula, we get the following distribution:

179,179,130,130,130,130,130,130,130,95,95,95,95,95,95,75,75,75,75,75,65

The mean ratio IQ is 108 (SD = 33). Thus Tao’s ratio IQ of 357 is 7.55 standard deviations above the mean.  Converting to the modern IQ scale where the mean and standard deviation are set at 100 and 15 respectively, this puts Tao at 213.

But this is way too high.  The normal curve predicts fewer than one in 190 billion cases should be above 202, so obviously an IQ of 213 is almost meaningless.

It shouldn’t be surprising that Tao’s ratio IQ is an absurd 7.55 standard deviations above the mean, because many people have argued that ratio IQs do not have a normal distribution.  But why not?  Because of non-linear brain development in childhood?  Because of sudden cognitive growth spurts?

And then it hit me.  I had another one of my flashes of genius 🙂

Pumpkin Person’s insight

The beauty of ratio IQs is that they are a true ratio scale, meaning not only are they based on age which are units with equal intervals (not exactly equal, since mental growth is faster at younger ages) but a true zero point.

Except they’re not.

When we are born, we are not 0 years old, but 0.75 years old, because we’ve been developing in the womb for 9 months.  Thus all of us need to add 0.75 years to the age all of the kids in the sample learned to read to get the true age:

4.75,4.75,6.25,6.25,6.25,6.25,6.25,6.25,6.25,8.25,8.25,8.25,8.25,8.25,8.25,10.25,10.25,10.25,10.25,10.25,11.75

Now the mean reading true age becomes 7.89.

When we calculate ratio IQs based on these true ages, we get the following distribution:

166,166,126,126,126,126,126,126,126,96,96,96,96,96,96,77,77,77,77,77,67

Now the mean becomes 107 and the standard deviation becomes 29.

To compare Tao to this new distribution, we must add 0.75 to the age when he learned to read, giving a true age of 2.75, compared to the average reading true age of 7.89, making Tao’s reading development 287% of the normal rate (ratio IQ 287).

This is 6.21 standard deviations above the true ratio IQ distribution, so on a modern scale where the mean and standard deviation are set to 100 and 15 respectively, his reading IQ would be 193.

The distribution is probably still not perfectly normal given the non-linear rate of mental growth in childhood, but I think it’s a lot better than it was before age was converted to true age.

According to this source , at age 8.3, Terence Tao scored 290 on the verbal section of the pre-1995 SAT(hat-tip to commenter Tenn for finding this data since my google searches for Tao’s verbal SATs turned up nothing) .

According to the book The Bell Curve (pge 694), if all American 17-year-olds took the old SAT in the 1980s (not just the college-bound elite) the mean verbal score would be 376 and the standard deviation (SD) would be 102.

Thus Tao scored 0.84 standard deviations below the average American-17-year-old (IQ 87 U.S. norms; IQ 84 U.S. white norms).  But given that he was only 8.83, he deserves a huge age bonus.

On the WISC-R Vocabulary subtest (the subtest most similar to the verbal SAT), an 8.8-year-old who scores about 0.84 SD below American 16.8-year-olds (16-25 percentile), is actually about 2.17 SD above the mean for his own age (98-99 percentile), implying a verbal IQ of 133 (U.S. norms) or 132 (U.S. white norms).

A verbal IQ of 133 is extremely high but it’s still 47 points below Tao’s math IQ of about 180.  I don’t know what the correlation between SAT verbal and math would be if the general population (not just the college bound segment) took the SAT, but let’s say it’s 0.67 (like the correlation between the verbal and performance scales on the WISC-R).

We would expect the average person with a math IQ of 180 to have a verbal IQ of 0.67(80) + 100 = 154, with 95% of all cases falling between 132 and 176.

Many people think it impossible that Richard Feynman could have obtained a valid IQ in the mid 120s as a child, but if the test was primarily verbal, we can see how it could have happened.

Apparently this blog has just been deemed worthy of StumbledUpon who has added content to their dynamic search engine, causing readership to nearly triple overnight, reaching roughly 2000 visitors in a single day on January 8, and over 2500 views.

Most of the traffic seems to be generated by my standard deviation article.

And of course this blog would be nothing without the comment section.  Wordpress generates a list of the most prolific recent commenters (the list includes me since technically I’m a commenter too :-))

The New York Times magazine reports:

By the spring of 1985, with a 9-year-old Tao splitting time between high school and nearby Flinders University, Billy and Grace took him on a three-week American tour to seek advice from top mathematicians and education experts. On the Baltimore campus of Johns Hopkins, they met with Julian Stanley, a Georgia-­born psychologist who founded the Center for Talented Youth there. Tao was one of the most talented math students Stanley ever tested — at 8 years old, Tao scored a 760 on the math portion of the SAT — but Stanley urged the couple to keep taking things slow and give their son’s emotional and social skills time to develop.

On page 422 of the book The Bell Curve it’s estimated that if virtually all American 17-yea-olds had taken the SAT in 1983 (not just the college bound ones), the mean math score would have been 411.   On page 425 a graph estimates that if all American 17-year-olds had taken the SAT in 1983, only about 0.7% would have scored 700+.

Assuming a roughly normal distribution, these two statistics imply that in 1983, if all 17-year-olds took the SAT, the math standard deviation would be 117.

Thus Tao at about age 8.8, scored 2.98 standard deviations above the average U.S. 17-year-old.

I don’t know where this would put him compared to U.S. 8.8 year-olds on the math SAT, but on the WISC-R IQ test, U.S. 8.67-8.997 year-olds who score in the top 37% of U.S. 16.67-16.997-year-olds on Arithmetic (the subtest most similar to the math SAT) narrowly make the top 0.4% among their own age group.  This suggests an age bonus of  2.33 standard deviations.

Thus Tao, was likely 5.31 standard deviations above the U.S. mean for his age, suggesting a math IQ of 180 (U.S. norms) and also 180 (U.S. white norms). Assuming roughly normal distributions, only about one in 21 million Americans should have math IQs this high or higher.

On page 292 of the book The g Factor, scholar Arthur Jensen writes:

There is a high degree of agreement among people when they are asked to rank occupation titles according to their impression of (1) the occupation’s socially perceived prestige, (2) the desirability (for whatever reason) of being employed in the occupation, and (3) the estimated level of “intelligence” needed to succeed in the occupation. When a number of people are asked to rank a large number of different occupations titles, from highest to lowest, on each of these standards, the mean rank for each occupation remains fairly constant.  The over-all rank order-correlations in various studies fall between .95 and .98.   The high consistency of rank order holds up across rankings by people from different occupations, social class backgrounds, industrialized countries, and generations.

From a Darwinian perspective, intelligence can be defined as the cognitive ability to adapt: to take whatever situation you’re in, and turn it around to your advantage.  People who spend their lives working in a good job, a job that others admire and wish they had, have generally turned their situation to their advantage.  By contrast, one who spends his life working in a job that others look down on and would never want to do, have generally failed to adapt, assuming one has the same goals as most people (and by definition most people do). Thus, one should expect a positive correlation between IQ and occupational status.

On page 293 Jensen writes:

The correlation of individuals’ IQs with occupational rank increases with age, ranging from 0.50 for young persons to about 0.70 for middle aged and older persons, whose career lines by then are well established.  

The relation of IQ to occupational level is not at all caused by differences in individuals’ IQs being determined by the differences in amount of education or the particular intellectual demands associated with different occupations.  This is proved by the fact that IQ, even when measured in childhood, is correlated about 0.70 with occupational level in later adulthood.

A 0.70 correlation is absolutely massive, especially by the standards of the social sciences. It’s roughly the correlation between IQ as measured in childhood and IQ as measured in adulthood.  If what Jensen is saying is true, one could make a very strong case that IQ is destiny.  The idea that a test given to a child could predict with that much accuracy, their place in society 40 years later is absolutely fascinating.  It’s almost as if life is a valid IQ test, and occupation is your score.

As a kid, an Indian woman in a sari drove from far, far away, to get to my school, just to test me, on the most expensive, in-depth IQ test the school board had.  A test so closely guarded and so carefully scored, no teacher was allowed to give it.  At the time I thought of Indian women in saris as fortune tellers because I would see one reading palms on downtown streets, so I remembered thinking of the school board Indian woman who asked me to play with blocks, jig-saw puzzles, and cartoon pictures that resembled tarot cards, as a fortune-teller too.  I was more right than I knew.  Childhood IQ predicts your future with alarming accuracy.

On the other hand, the correlation between IQ (both in childhood and adulthood) and older adult occupation sounds too high to be true, especially if the correlation could be forced to fit a bivariate normal distribution and extended to the extremes.

For example, there are 76.4 million baby boomers.  That means the baby-boomer with the best job is +5.53 Standard Deviations above the mean of a normalized occupation distribution.  This implies an IQ that is 0.7(5.53) = 3.87 SD above the mean: IQ 158, a truly jaw-dropping figure.

So who has the best job in America?  Apparently it’s not the president since White House occupants seem to average IQs around 130.  Maybe this is a case where the linear models I love so much, simply don’t work, no matter how much I want them to.

It’s also a bit strange that childhood IQ would correlate as much with older adult occupation as adult IQ itself does.  I hope this isn’t because socioeconomic background is influencing both childhood IQ and later adult occupation.

I know I said I would analyze commenter “Animekitty” and it would have made for a fascinating topic, however this commenter strikes me as a very nice sensitive soul who has been so incredibly open with us, and I don’t want to exploit that just to increase the readership of my blog, so there are no plans to discuss him.

Meanwhile  I do have future plans to estimate the IQ of Clark Ashton Smith and I received a request to estimate the IQ of Tim Leary.