Consider a binary classification problem with an ensemble learning algorithm that uses simple majority voting among K learned hypotheses. Suppose that each hypothesis has error E and that the errors made by each hypothesis are independent of the others. Calculate a formula for the error of the ensemble algorithm in terms of K and E$,$ and evaluate it for the cases where K $=5,11,$ and $21$ and E$=0\mathrm{.}1,0\mathrm{.}2,$ and $0\mathrm{.}4.$ If the independence assumption is removed, is it possible for the ensemble error to be worse than E$?$