at 10:43, in the Fourier transform of phi(z), value of "phi(z)dz" is used as "p(x)q(y)dxdy". This is exactly that was argued as wrong just before. Justification? Explanation?
meon youtube I guess coz in integral all the infinite pairs of x and y are included so for a perticular Z with its set of Paris of X and Y values of probabilities of all such probabilities will be added thus giving true probability of z in dz interval
at 26:44, I understand integration variable is dummy, but are limits of integration x1,min, x2,min etc also same? isn't it loss of generality? x1,x2 were uncorrelated...
As per my current understanding, the central limit theorem requires that xi is identical independent distributed random variables (IID). So all xi's are derived from the same probability distribution function so the p(xi)=p(x) and the limits are also same. Hence the prof took all the things and raised p(x) to the power of N. Please correct me if I'm wrong
at 10:43, in the Fourier transform of phi(z), value of "phi(z)dz" is used as "p(x)q(y)dxdy". This is exactly that was argued as wrong just before. Justification? Explanation?
meon youtube I guess coz in integral all the infinite pairs of x and y are included so for a perticular Z with its set of Paris of X and Y values of probabilities of all such probabilities will be added thus giving true probability of z in dz interval
I just guess that’s the reason
Same question
at 26:44, I understand integration variable is dummy, but are limits of integration x1,min, x2,min etc also same? isn't it loss of generality? x1,x2 were uncorrelated...
can someone please answer this question
As per my current understanding, the central limit theorem requires that xi is identical independent distributed random variables (IID). So all xi's are derived from the same probability distribution function so the p(xi)=p(x) and the limits are also same. Hence the prof took all the things and raised p(x) to the power of N.
Please correct me if I'm wrong