Derive the posterior distribution of N up to a proportionality constant. Besure to specify the bounds on the parameter space ofNin your posterior distribution

Suppose for a binary sampling problem we plan on using a 1miform, or Beta(1,l) prior for the population proportion 15'. Perhaps our reasoning is that this represents \"no prior information about 6'\". However, some people like to look at proportions on the log-odds scale, that is, they are interested in \"y = log () . Via Monte-Carlo sampling or otherwise nd the prior distribution for qr that is induced by the uniform prior for 3. Is this prior informative about 1r