So here is the headache: Remember Edward Thorp and ‘Beat the Dealer?’ He changed things over showing an advantage. Here is another one. You can beat randomness. Randomness in Roulette has characteristics. You discover these characteristics while charting their current state in the form of parallel results for each spin. They relate to the concept of now. You can guess the now state. You should find that the characteristics of randomness include dominance, trends, patterns, and global effects. It’s possible to make an educated guess at these characteristics, to establish a line of effectiveness. Effectiveness exists in three states, works very well, flat lines as temporarily indecisive of any state, and works very badly. Works very badly can be recognized so that the educated guess may be selected as the opposite bet selection, thus turning around the effectiveness state. Playing experience is the process that turns this into an advantage.

]]>Garret

]]>That’s a good question. As you’d expect, a lot has been written on the meaning of probability in quantum mechanics. I read up on it a bit a long time ago, but it’s all pretty hazy in my mind right now. If I were to start looking into this again (which I certainly can’t do this week), I’d probably start by reminding myself what John Baez has to say on the subject at

http://math.ucr.edu/home/baez/bayes.html

but I don’t remember if it really gets into the question you’re asking.

]]>That should have read

bra(phi) ket(psi) = 0.5

]]>Sorry for wandering in on this thread at such a late stage, I just found it because I was wondering about a problem which I’ve been scratching my head about.

The question is, in quantum mechanics, how does one describe – particularly to an undergraduate! – the physical meaning of a relation such as

= 0.5

*without* invoking any sort of frequentist scenario? (I’m sure this must have been done to death in the literature if you can just point me in the right direction please do!)

Thanks

Garret Cotter

]]>1. Interpretation of probability

2. Use of statistical techniques

I’m a diehard Bayesian on item #1, but I’m fervently indifferent about #2. I think that frequentism is incoherent and silly as a way of understanding philosophically what probabilities mean (#1), but that doesn’t mean that frequentist techniques in statistics are invalid (#2). On the contrary, a frequentist confidence interval is a perfectly valid answer to a particular question, and a Bayesian credible region is a perfectly valid answer to a different question.

I cowrote a paper once analyzing a particular data set from both Bayesian and frequentist points of view, to highlight the similarities and differences (http://arxiv.org/abs/astro-ph/0111010).

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