function p = met_pDwb(y,y1,sv)
%
% p = met_pDwb(y,y1,sv)
%
% Tutorial function for arg min in the problem7. 
% y, y1 are [N x 1] - vectors
% sv is a scalar, value of standard deviation for gaussian noise.
% p is a pdf value, diven all arguments, scalar.
%
% Example
% met_pDwb([1,2,3],[4,5,6],5)
%
N = length(y);
p = 1/((sv*sqrt(2*pi))^N)*exp(-sumsqr(y1-y)/(2*(sv^2)));
return