Ok, note added.
Good one.
I chose the decibel scale instead of using bits because bits were a bit awkward when the probabilities were close to 50%. From 0 bits to 1 the probability jumps 16.666%, and the odds doubles, but with decibels the first jump is about 6%, and doubles the odds around 3 decibels, and multiplies them by 10 in exactly 10 decibels.
Exactly, I used approximations on purpose, but the real approximated value in this case is the 1%. The ratio that actually gets -20 dB is 1:100.
I felt that getting approximated but round results was worth the imprecision. If I used values like -19.96 on the table, then people without the patience to handle maths wouldn't be able to use it as well.
Should I explain about the imprecisions of this table better in the article?
Ok. Corrected it, and tried to fix my fonts. I don't know if I did it right.
This is an effort to make Bayes' Theorem available to people without heavy math skills. It is possible that this has already been invented, because it is just a direct result of expanding something I read at Yudkowsky’s Intuitive Explanation of Bayes Theorem. In that case, excuse me for reinventing the wheel. Also, English is my second language.
When I read Yudkowsky’s Intuitive Explanation of Bayes Theorem, the notion of using decibels to measure the likelihood ratio of additional evidence struck me as extremely intuitive. But in the article, the notion was just a little footnote, and I wanted to check if this could be used to simplify the theorem.
It is harder to... (read 593 more words →)
Greetings, everyone.
My name is Francisco, and I am from Malaga, Spain. I am a dabbling rationalist, and a programmer/troubleshooter.
I started walking the path of rationality when I started keeping track of good luck/normal luck/bad luck events in order to check if Murphy's law was actually true, and then wondering why people actually believed in it. Later, I started reading about fallacies, and I finally arrived at LW via HMPOR, like many people.
I am currently reading my way through the Sequences, but my current project is to make Bayes' theorem more accessible to people without math backgrounds. I have a couple of ideas that I'd like to refine and share at this community, even if English is my second language.
I don't think that RA actually moved the goalposts. The goal is exactly the same: "Men have better technical abilities than women, so they should get paid more for the same engineering jobs."
The point that WA actually changed was from "Men and women are just as well suited to technical careers as each other!", which he conceded, to "If men really are better, they'll get raises and promotions on their own merit, not merely by virtue of being male."... But these points aren't located in the goal. They are points in the middle of the field, parts of a discussion. Losing one of those points shouldn't mean losing the whole discussion.
An example of actual goalpost-moving should be from "Men have better technical abilities than women, so they should get paid more for the same engineering jobs." to "People who have better technical abilities should get paid more for the same engineering jobs".
Muy buenas a todos. Yo tambien estoy interesado en traducir las secuencias al castellano. Estoy especialmente interesado en hacer llegar estos conceptos a la mayor cantidad de personas posible, y que el idioma no sea un impedimento. ¿Hay algun grupo de traducción existente?
Ok, I changed it. It certainly seems more intituitive this way.