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Comment author: orthonormal 19 January 2012 06:53:38PM 0 points [-]

If I decide whether you win or lose by drawing a random number from 1 to 60 in a symmetric fashion, then rolling a 60-sided die and comparing the result to the number I drew, this is the same random variable as a single fair coinflip. Unless you are playing multiple times (in which case you'll experience higher variance from the correlation) or you have a reason to suspect an asymmetric probability distribution of green vs. blue, the two gambles will have the exact same effect in your utility function.

The above paragraph is mathematically rigorous. You should not disagree unless you find a mathematical error.

Comment author: kim0 22 January 2012 05:00:05PM 0 points [-]

And yet again I am reminded why I do not frequent this supposedly rational forum more. Rationality swishes by over most peoples head here, except for a few really smart ones. You people make it too complicated. You write too much. Lots of these supposedly deep intellectual problems have quite simple answers, such as this Ellsberg paradox. You just have to look and think a little outside their boxes to solve them, or see that they are unsolvable, or that they are wrong questions.

I will yet again go away, to solve more useful and interesting problems on my own.

Oh, and Orthonormal, here is my correct final answer to you: You do not understand me, and this is your fault.

Comment author: orthonormal 19 January 2012 05:28:26AM 0 points [-]

Like I said below, write out the actual random variables you use as a Bayesian: they have identical distributions if the mean of your green:blue prior is 30 to 30.

There is literally no sane justification for the "paradox" other than updating on the problem statement to have an unbalanced posterior estimate of green vs. blue.

Comment author: kim0 19 January 2012 07:55:52AM -1 points [-]

Bayesian reasoning is for maximizing the probability of being right. Kelly´s criterion is for maximizing aggregated value.

And yet again, the distributions of the probabilities are different, because they have different variance, and difference in variance give different aggregated value, which is what people tend to try to optimize.

Aggregating value in this case is to get more pies, and fewer boots to the head. Pies are of no value to you when you are dead from boots to the head, and this is the root cause for preferring lower variance.

This isn´t much of a discussion when you just ignore and deny my argument instead of trying to understand it.

Comment author: orthonormal 18 January 2012 01:14:55AM 0 points [-]

I think what you're saying is just that humans are risk-averse, and so a gamble with lower variance is preferable to one with higher variance (and the same mean)... but if the number of green vs. blue is randomly determined with expected value 30 to 30, then it has the same variance. You need to involve something more (like the intentional stance) to explain the paradox.

Comment author: kim0 18 January 2012 01:55:28PM *  2 points [-]

No, because expected value is not the same thing as variance.

Betting on red gives 1/3 winnings, exactly.

Betting on green gives 1/3 +/- x winnings, and this is a variance, which is bad.

Comment author: kim0 17 January 2012 09:23:59AM 1 point [-]

Preferring red is rational, because it is a known amount of risk, while each of the other two colours have unknown risks.

This is according to Kellys criterion and Darwinian evolution. Negative outcomes outweigh positive ones because negative ones lead to sickness and death through starvation, poorness, and kicks in the head.

This is only valid in the beginning, because when the experiment is repeated, the probabilities of blue and green become clearer.

Comment author: Elizabeth 08 February 2011 06:43:39AM *  38 points [-]

I don't know if anyone can help me with this, but how do I tell the difference between flirting and friendliness? I grew up in pretty much total social isolation from peers, so neither really ever happened, and when they happen now I can't tell which is which. Also, how do you go from talking to someone at the beginning/end of class (or other activity) to actually being the kind of friends who see each other elsewhere and do activities together?

Edit: Thank you, this is good advice. Does anyone have any advice on how to tell with women? I'm bi, and more interested in women, and they are much harder to read than men on the subject, because women's behavior with female friends is often fairly flirty to begin with.

Comment author: kim0 08 February 2011 07:59:19AM 12 points [-]

There often is not any difference at all between flirting and friendliness. People vary very much in their ways. And yet we are supposed to easily tell the difference, with threat of imprisonment for failing.

The main effects I have seen and experienced, is that flirting typically involve more eye contact, and that a lot of people flirt while denying they do it, and refusing to to tell what they would do if they really flirted, and disparaging others for not knowing the difference.

My experience is also that ordinary people are much more direct and clear in the difference between flirting and friendship, while academic people muddle it.

Comment author: Daniel_Burfoot 01 September 2010 04:18:01PM 4 points [-]

Can you expand on this? Do you think your experience is typical?

Comment author: kim0 03 September 2010 08:19:18AM 4 points [-]

Most places I have worked, the reputation of the job has been quite different from the actual job. I have compared my experiences with those of friends and colleagues, and they are relatively similar. Having a M.Sc. in physics and lots of programming experience made it possible for me to have more different kinds of engineering jobs, and thus more varied experience.

My conclusion is that the anthropic principle holds for me in the work place, so that each time I experience Dilbertesque situations, they are representative of typical work situations. So yes, I do think my work situation is typical.

My current job doing statistical analysis for stock analysts pay $ 73 000, while the average pay elsewhere is $ 120 000.

Comment author: Daniel_Burfoot 01 September 2010 02:48:18AM 4 points [-]

Anyone here working as a quant in the finance industry, and have advice for people thinking about going into the field?

Comment author: kim0 01 September 2010 09:08:23AM 3 points [-]

I am, and I am planning to leave it to get a higher more average pay. From my viewpoint, it is terribly overrated and undervalued.

Comment author: kim0 22 June 2010 07:34:49AM 1 point [-]

That was a damn good article!

It was short, to the point, and based on real data, and useful as well. So unlike the polite verbiage of karma whores. Even William of Ockham would have been proud of you.

Kim0+

In response to comment by [deleted] on Open Thread: May 2010
Comment author: Jack 01 May 2010 10:22:47PM 1 point [-]

Concepts like species, subspecies and faimily are also constructs that are just about as arbitrary as race.

This is a matter of much dispute and a lot of confusion. See here.

In response to comment by Jack on Open Thread: May 2010
Comment author: kim0 02 May 2010 12:52:36PM 3 points [-]

I wondered how humans are grouped, so I got some genes from the world, and did an eigenvalue analysis, and this is what i found:

http://kim.oyhus.no/EigenGenes.html

As you can see, humans are indeed clustered in subspecies.

Comment author: kim0 02 April 2010 06:59:34AM *  1 point [-]

Many-Worlds explained, with pretty pictures.

http://kim.oyhus.no/QM_explaining_many-worlds.html

The story about how I deduced the Many-Worlds interpretation, with pictures instead of formulas.

Enjoy!

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