
www.Usenet.com
| <-- __Chronological__ --> | <-- __Thread__ --> |
In article <[EMAIL PROTECTED]>, "walala" <[EMAIL PROTECTED]> wrote: > If I already know a prior that my data distribution should follow the shape > of Laplacian distribution... the data obtained from measurement is of course > a little off(not very symmtrical), how can I make the measured data more > Laplacian distribution like(make it at least a little more symmtrical)? > > Can anybody give me an example or detailed explanation? I am kind of afraid > of statistics... :=) Lets see if I understand. Your data does not follow your prior beliefs. Therefore the data is wrong, and you want to know how to modify said data so that it does exactly what you want. This makes sense - in a very distorted way. Why did you bother with measuring that blasted data in the first place? You have already decided the result. Measurements just get in the way. Please start by reading the book "How to lie with Statistics". Then return to your data, and learn from it. Is it just random noise that has given your data this property you did not expect? Or is this an indication of a problem in your measurement? Perhaps it indicates something wrong with the theory? Perhaps another factor distorts the data? Maybe your sample is just too small! I can summarize the strong suggestions I give to my students who deal with data in three words: Plot - think - learn. Only after that do I tell them to do any actual modeling, or use their data in any way. HTH, John D'Errico -- There are no questions "?" about my real address. The best material model of a cat is another, or preferably the same, cat. A. Rosenblueth, Philosophy of Science, 1945
| <-- __Chronological__ --> | <-- __Thread__ --> |