Since \max \sigma_P^2 = \max P(1-P) = 0.25 at p = 0.5, we can arbitrarily set p=\overline{p} = 0.5, calculate \sigma_{P}, \sigma_\overline{p}, and z_\gamma\sigma_\overline{p} to obtain the maximum margin of error for P at a given confidence level \gamma and sample size n, even before having actual results.  With p=0.5,n=1013
