IQ Tails of Race & Gender

Fear not, I am not going to perform any analysis proving the intellectual superiority of any race or gender. Also, as a 100% Spaniard (I need to check on that though) I do not belong to the “elite” of ethnics groups disputing supremacy, namely: Northern Europeans, Jews and Far-East Asians and, quite frankly, I feel kinda good about it since I’d rather stick to the Latin Lover stereotype which, by all means, it is true.

Recently I came across a video titled Steven Pinker – Jews, Genes and Intelligence. Typically I would have disregarded this video as your standard white supremacy internet rhetoric however, I know Steven Pinker from his published works and achievements, and he is no small fish in the Psychology and Cognitive Science world. That is why I decided to give a shot to his video to see what’s what until he began talking about statistics. These are his words:

“…Jewish achievements might have an explanation on another fact that has long been known; that Jewish score on average higher on IQ tests than any ethnic group for what there’s comparable data. Their mean IQ is between 108 and 115, the mean of the European population is by definition a hundred which means that the Jewish average is a whole standard deviation higher than the [European] average… Importantly, even if the effect is moderate on average it’s a mathematical fact in Normal Distributions, that is Bell’s Curves, that small effects in the average can translate into huge effects at the extreme… So with one standard deviation difference between groups a score that is three standard deviation above the mean in the higher distribution is four standard deviations in the lower distribution which means there are 42 times as many people at that cut off.” – Steven Pinker

In short, according to Steven Pinker there are 42 times more chances for a Jewish baby to be born an IQ genius than for an European one… But, is that really so?

If you play with your Prior you’ll go blind

And thus, the Huffington Post predicted a 98% probability for Hillary Clinton to be the next President of the United States. Amen… Let’s tease them a little bit, shall we?

My Bayesian friends, I understand playing with your priors is a very joyful activity but you see, it leads to blindness. It allows you to believe, let me cap & bold this one, BELIEVE that Hillary’s chances to be the next President of United States were 98%! No wonder that betting sites favored heavily Hillary’s side days before the election! I mean 98%! Who wouldn’t put some money there. Right?

But you know, a 98% probability coming from a Bayesian means very little unless, of course, they do some math pirouette to guarantee that the probability has frequentist properties, but then, if they do that, why bother going Bayesian in the first place?

If a frequentist tells you there is 98% probability for an event to happen he/she means that 98 out of 100 times where you find yourself in a situation like where the event is taking place the event will occur. Now, if a Bayesian tells you there is 98% probability he/she means that this is his/her degree of believe (wot?) on the event to happen… Amen again.

In other words, Bayesian results are as credible as the beliefs of the Bayesian statistician making the calculations, now we can understand why they calculate credible intervals instead confidence ones.

If we check on the Huffpo methodology we can read:

Many Bayesian models ― including the Pollster averaging model as it’s implemented for our charts ― use “uninformed” priors that don’t affect the model or provide any background information.

However, we do use information from previous elections in these priors to make predictions in our presidential model.

Ba dum tsssss

Much has been written on the pros and cons of going Bayesian and how evil Frequentists are, but this amazing Bayesian result from Huffpo was just too good to let go as a beautiful example of how blind you can go when playing with your priors.

Social Network Analysis & GOP Verbal Attacks

Not that I know anything about the GOP debates or candidates, but I casually saw in a CNN post this nice visualization of verbal attacks during the RL GOP Debate, and I thought that I would do a little SNA and try to draw conclusions on the debate WITHOUT actually having seen it…

let’s see how it goes and, please, if you’ve seen the debate and know better than me, let me know if I am very wrong 🙂

Priesthood, Pedophilia & Homosexuality

• At most 22 percent of catholic priests in the USA are homosexuals.
• Homosexual men in the USA, as a group, molest children at a rate at least 15 times higher than heterosexual men.

One  asteroid rubs Earth, a meteorite crashes on Russia and, a few days later, Pope Benedict XVI took the cosmic message and resigned. Nonetheless many people question the true reason for his resignation alleging that it has nothing to do with fatigue but rather with homosexuality networks within the Church (CNN guest claiming a 50% of homosexuals among priests) and unresolved pedophilia scandals. So I took a look at this percentage with our best friend when it comes to politically incorrect statistics; Bayes’ Theorem, and I got the results displayed above.

I know, I know, the numbers are pretty crazy, but they are based on data fetched from official sources and, before going into the details, let me play sociologist. Although homosexuals, as a group, molest children at higher rates than heterosexuals it is very important to realize that this does not necessarily mean homosexuals are more prone towards this behavior, assuming this might constitute an ecological fallacy, in this case it makes more sense that this outcome obeys to the fact that young boys are way less protected by parents than young girls and predators take advantage of this.

The Calculations

To estimate the rate of homosexuals among catholic priests we will first estimate how much more likely are male homosexuals to engage in pederasty compared to male heterosexuals, then we will use this result join with the by gender percentage of children abused by catholic priests (81 percent of the victims were males in the USA) to calculate the final figure.

My Baby Shot Gun Control Me Down… with Statistics

Best way to lie? Statistics, no question about it, and if you don’t believe me I can show you some statistics that support this point… or any other point for that matter. But statistics are even better to lie to yourself; the same way different people see different things when they look at clouds, people also see different things when they look at data, and if there is one endless debate where people reinforce their beliefs with cherry picked data that debate is gun control.

Talking about cherry picking, let’s check at the The Young Turks‘ argument to support stricter gun control in the USA: “ban guns like Japan and you have 2 gun related homicides, don’t ban guns and you have 10,225 gun related homicides”. And they explain their point in a way that you’d better not to dare to disagree. Sure they could have compared data from 2007 where the USA had 9,146 gun related homicides and Brazil 34,678 mentioning that Brazil has much tighter gun control laws than the USA but, unfortunately, this is the way politics and media works; it does not matter if you are right or wrong, only if you look right or wrong. But let’s analyze some data and a few more examples of how information is presented to us.

Racial Profiling vs Description of the Suspect

You are a policeman in a car chase of a criminal wearing globes and a mask, the most likely scenario according to statistics is that the criminal is a white person. Then the car stops in front of a bar and the criminal rushes in getting rid of the globes, mask and changing his clothing. You enter the bar and you see a white guy and a non-white guy. Who should you question first? The non-white guy. Racism? No, Bayes’ Theorem.

According to the US Department of Justice racial profiling is defined as:

Any police-initiated action that relies on the race, ethnicity, or national origin rather than the behavior of an individual or information that leads the police to a particular individual who has been identified as being, or having been, engaged in criminal activity.

A key part in this definition is where it justifies the police-initiated action when there is information that leads to a particular individual. In other words, if there are witnesses saying that the thief was a barefooted blond white little girl wearing a green blouse and a red tutu then going after girls looking like that would not be considered racial profiling but simply checking on the description of the suspect.

But how about if the police-initiated action is not based on information coming from witnesses but in information coming from statistics? Is information coming from statistics still information according to the definition of the US Department?

Israel vs Palestine: Who is to blame according to statistics?

Data seems to suggest that, though Palestinians are the ones more actively looking for troubles they are also the ones more actively looking for solutions, whereas Israelis seem to adopt a more nonchalant attitude either way.

When Hell opens its gates in the Holly Land this is how the story goes most of the time: