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 🙂
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.
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.
French psychologist Michel Gauquelin gained notoriety in the 50’s after publishing data showing that sportsmen were born in a non random fashion when considering the movement of planet Mars, the nicknamed Mars Effect has been the core of passionate discussions over its statistical validity since then but, beyond whether this effect truly holds or not, there are many reasons why genuine statistically significant data can be found in the astrology world, so we’d do better not to ignore planets and stars entirely.
We humans develop efficient strategies in our daily life that are useful for most situations, for example, if we see dark clouds and a few moments later it rains we associate dark clouds with rain and, voilà, next time we see dark clouds we take measures. The problem begins when we break a leg right after seeing a black cat, our association machine, a.k.a brain, does its magic and next time we see a black cat we take measures too. But you know what? The brain is right!
What is not so right is human difficulties to removed associations once they are set in our brains, a.k.a stubbornness. We humans develop all sort of strategies too keep our associations alive and demand extraordinary amounts of evidences to break them yet, even when those evidences are presented, we keep fighting them by doubting the methodology or the honesty of the persons bringing them up. There might be evolutionary advantages explaining why we create associations so easily but cannot break them with the same ease, but whatever the reasons are the problem only worsens when in some cases our stubbornness makes the associations come true! And that is what astrology is all about. These are a few examples of how astrology makes spurious associations come true: Continue reading
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? Continue reading
Alea Deum 