Well, am not a great fan of these techniques, but I can safely say that I have been fortunate enough to know people who plays these techniques with greater amount of success and have learnt a lot from them. As some of you have pointed out that this is a subject which is like "I will tell you, but have to kill you", I have decided to post the knowledge I have gathered from some of my close friends who practice this technique. I am not worried about them killing me, as I am anyway counting my days
Standard deviation
Now anyone who wants to read something about standard deviation, I would suggest reading this wonderful article from our mathematician friend Bayes
http://www.rouletteforum.cc/index.php?topic=1093.0
Things can't get simpler than that and I am not going to explain here what 2SD means or what 3SD means. That will essentially defeat the purpose of this thread. And moreover, I can't put that simpler than what Bayes has put in his thread. What I will explain is the practical applicability of this in roulette in simple English with some examples and explain the common fallacies and pitfalls that you should avoid. As in all the threads that I have initiated, you need to develop your own strategy around it, eventhough I will touch upon a couple of methods of using it. In fact one who would like to understand statistics in a fun and easy way, I would recommend the book Cartoon guide to statistics by Larry Gonick. Very nice read , but don't expect to become a statistician after that
Regression to mean
The explanation goes it is the phenomenon in which if a variable is extreme on its first measurement, it will tend to be closer to the average on its second measurement—and, paradoxically, if it is extreme on its second measurement, it will tend to have been closer to the average on its first. Using Regression, as with any statistic concepts, you cannot be certain of something to happen, but you can certainly say that it will happen within a degree of predictability.
Simple applicability in roulette could be (ofcourse some people might disagree as statistics is common sense and what is common sense is always questionable), you see that there are 10 Reds in a row, then in the next 10 spins, there is a higher degree of probability for a balanced mix of reds and blacks to be present. Often people misunderstand that the next 10 spins will have more blacks than reds or completely black so that it will all even out. NO! That's not the case. Regression to the mean will just imply that the next set of 10 spins will have a higher chance of a mix of blacks and reds. Again note, nothing is certain.
Now in my next post, I shall explain some concepts that one should take into consideration while practicing regression to the mean.
Standard deviation
Now anyone who wants to read something about standard deviation, I would suggest reading this wonderful article from our mathematician friend Bayes
http://www.rouletteforum.cc/index.php?topic=1093.0
Things can't get simpler than that and I am not going to explain here what 2SD means or what 3SD means. That will essentially defeat the purpose of this thread. And moreover, I can't put that simpler than what Bayes has put in his thread. What I will explain is the practical applicability of this in roulette in simple English with some examples and explain the common fallacies and pitfalls that you should avoid. As in all the threads that I have initiated, you need to develop your own strategy around it, eventhough I will touch upon a couple of methods of using it. In fact one who would like to understand statistics in a fun and easy way, I would recommend the book Cartoon guide to statistics by Larry Gonick. Very nice read , but don't expect to become a statistician after that
Regression to mean
The explanation goes it is the phenomenon in which if a variable is extreme on its first measurement, it will tend to be closer to the average on its second measurement—and, paradoxically, if it is extreme on its second measurement, it will tend to have been closer to the average on its first. Using Regression, as with any statistic concepts, you cannot be certain of something to happen, but you can certainly say that it will happen within a degree of predictability.
Simple applicability in roulette could be (ofcourse some people might disagree as statistics is common sense and what is common sense is always questionable), you see that there are 10 Reds in a row, then in the next 10 spins, there is a higher degree of probability for a balanced mix of reds and blacks to be present. Often people misunderstand that the next 10 spins will have more blacks than reds or completely black so that it will all even out. NO! That's not the case. Regression to the mean will just imply that the next set of 10 spins will have a higher chance of a mix of blacks and reds. Again note, nothing is certain.
Now in my next post, I shall explain some concepts that one should take into consideration while practicing regression to the mean.