How'd they calculate E[Y^2] ? I'm stuck on this too. Found this old thread, thought not to create a new one. Can someone please help?
E(Y^2)=Var(Y)+E(Y)^2, from part (1) we know that E(Y)=50 now for variance X follow N(0,1) therefore X^2 follow chi square distribution with 1 degree of freedom , thus Y follows chi square with 50 degrees of freedom (since Xi's are independent) and we know that mean of chi square distribution is 2K(where K is the degree of freedom) thus Var(Y)=100 and E(Y^2)=100+50^2=2600