Reality Doesn’t Rely on Narratives
Or, why highly intelligent women marry men less intelligent than them
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Today, let’s talk about statistics. Especially why it’s so hard to wrap our head around some of its concepts. In this post we’ll learn how our “logical brain” often tries to add reasons where none exist, and why it’s so hard to understand a phenomenon without causal reasoning.
We’ll start with the following statement:
“Highly intelligent women tend to marry men who are less intelligent than them.”
I often use an outrageous statement like this at parties. “You know I came across this interesting study which found that high IQ women tend to marry men who are somewhat less intelligent than they are. It’s fascinating!” I can get a good conversation started by asking for an explanation, to which people readily oblige.
Whenever we try to explain such statements, we spontaneously ask ourselves what might be the possible reason for this to happen, i.e, what was the “cause” for this “effect”.
The popular reasons I usually hear are: highly intelligent men don’t want an intelligent wife to steal their thunder, hence the intelligent women have to settle for less intelligent men. Or, high IQ women want to avoid competition of equally intelligent men (which is exactly the opposite of the previous argument). Or, my favourite: unlike the low IQ men, high IQ men aren’t charmers.
If you try this at a party, I’m sure you’ll come across more far-fetched explanations. It’s good fun. Now consider this statement:
“The correlation between the intelligent scores of spouses is less than perfect.”
This is a (mathematical and) boring statement. But it’s a true statement. Interestingly, this lacklustre statement and the above (interesting) statement point towards more or less the same thing. Before I explain that, let’s understand what’s correlation. A slight detour:
If you take a large number of random earthlings (say ~1,000,000) from all age groups, genders, races, cultures, etc., and plot the relationship between their height and weight, the graph would look something like this.
While there is some pattern, we cannot find a “perfect relationship” between the height and weight of a person. While virtually every three-year-old will be lighter and shorter than every grown man, not all grown men or three-year-olds of the same height will weigh the same. In technical terms, the correlation coefficient between height and weight is less than 1 (not perfect) but not 0 (i.e., there is some correlation).
But if we take another example where we plot the number of cricket matches India wins every year against the total Coca-Cola consumption in the country, the graph would be all over the place. There is no correlation, i.e., the correlation coefficient is zero.
The third use case, where two entities have perfect correlation (i.e., correlation coefficient is either 1 or -1), is often pretty obvious. For example, the relationship between Celsius value and Fahrenheit value of temperature. If you plot them on a graph, you’ll get a straight line.
Similarly, an example of a negative correlation (correlation coefficient of -1) is the relationship between speed of a vehicle and the time it takes to reach from point A to B. If speed increased, time decreases (given everything else remains the same).
Now, coming back to the case at hand. On the basis of what we’ve learnt about correlation, the statement, “The correlation between the intelligent scores of spouses is less than perfect,” means: if we take a large enough sample of couples and plot the relationship between their individual IQs on a graph, we might see some pattern (positive/negative correlation), but we won’t get a straight line (i.e., they have less than perfect correlation).
In other words, if the correlation between the IQ of spouses is less than perfect and if we believe men and women do not differ in intelligence, then it is a mathematical inevitability that highly intelligent women will be married to men who are on average less intelligent than they are — and vice versa. Meaning, even high IQ men tend to marry women who are less intelligent than they are.
This essentially means that the chances of two partners representing the top 1% in terms of intelligence (or as a matter of fact, any characteristics whatsoever) is far smaller than one partner representing the top 1% and the other the bottom 99% — thereby bringing down their combined intelligence towards 50% (or, towards the mean). This very phenomenon is known as Regression Towards the Mean.
Regression towards the mean is what explains why high IQ people marry people with average intelligence. It has nothing to do with culture, fear, relationship quality, stigma, social media, personality, jealousy, charm, charisma, etc. It’s a purely mathematical phenomenon—one that cannot be expressed with “reasoning”.
In fact, correlation and regression are not two concepts — they are different perspectives on the same concept. Daniel Kahneman, the father of behavioural economics, observes that whenever the correlation between two entities is imperfect, there will be regression towards the mean. That’s just how nature works.
But even after all the explanation, something feels off. Your mind is strongly biased toward causal explanations and cannot swallow the reason for something being “mere statistics.” That’s the limit of our reasoning.
Regression has an explanation, but it doesn’t have a cause. No matter what reason you attach (believable or not), it will be wrong. So, don’t bother.
Regression confounds me. The only way I tame my “reasoning urges” is by taking stock of The Green Lumber Fallacy: just because I cannot explain something, doesn’t make it less true.
Reality doesn’t rely on narratives, humans do. When you have action (and result), you don’t need explanation (of the cause and effect).
Therefore, next time someone tries to explain why ice-cream causes heatstroke, or why depressed children treated with energy drinks improve significantly over a couple of months, humour them. But don’t try to correct them unless you never want to be invited to parties ever again.
Interesting Finds
Maths is the best way to make sense of the world. According to a recent study, 36 percent of college students don’t significantly improve in critical thinking during their four-year tenure. Students should take more maths and science than is required. Because there’s no better tool than quantitative thinking to process the information that is thrown by the world at us.
Kerala accounts for two-thirds of new infections in India. Despite having only 3 per cent of the population and a vaccination rate that, at 70 per cent, is higher than the national average, Kerala is in a fire-fighting mode. Is it the festivals, the population density, or a lax approach to quarantine? Or perhaps Kerala is simply honest about its figures, or so good at containing the disease last time round that too few people now have antibodies?
India has made big investments in Afghanistan. About $3Bn. Why would anyone in their right mind make such sizeable investments in a wartorn country? What good does it do, when we know there’s a high likelihood of failure? Well, believe it or not, there’s actually some merit to the madness.
Current models of remote education are inefficient for learning, teaching and productivity. Students learn better when they move their bodies—instead of sitting still at their desks. Teachers, parents and students should all change their expectations of what being “study time” looks like. Walking, running or dancing may not seem related to studying, but these activities often help kids do their best thinking.
The idea of Afghan freedom is often linked with India. The building of the Afghan Parliament was testimony to India’s democratic traditions. An estimated 11,000 Afghans study in India, of which 35 per cent are believed to be women. Many of the students are now in limbo, with their embassy shut and their visas no longer valid. Universities have tried to pitch in. The O.P. Jindal Global University (JGU) has launched special fellowships, offering “credible educational alternatives” to Afghanistan students. At IIT Delhi, there is a helpline that is helping Afghan students find a place on campus. And Pune University is offering counselling.
India needs to create 300 million jobs between 2015 and 2050. The idea of self-reflective and anxious millennials is something of a trope used to mischaracterise the generation. But real financial and economic anxiety exists among millennials, particularly those who have to support their families and find or maintain stable employment.
Timeless Insight
99 out of 100 startups fail, but with a large number of startups out there, a lot of them are bound to enjoy stupid success. One of them might be yours.
— Why You Should Plan For Miracles
Book I’m Reading
Data can tell you that the people who took a medicine recovered faster than those who did not take it, but they can’t tell you why. Maybe those who took the medicine did so because they could afford it and would have recovered just as fast without it.
— Judea Pearl, The Book of Why
Tiny Thought
Your three most undervalued F’s are: freedom, friendship, and flow state.
Before You Go…
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I’ll see you next Sunday,
Abhishek 👋
PS: All typos are intentional and I take no responsibility whatsoever! 😬