Basic Monte Carlo Approximation

function Value = Approx_Integral(F, x_Min, x_Max)
    Approximation = [];
    if(x_Min <= x_Max)
        %f_Min = fminbnd(F,x_Min,x_Max) this wasn't returning the right
        %values and I'm not sure why
        x=x_Min:.00001:x_Max;
        f_Min = min(F(x));
        f_Max = max(F(x));
        for k = 1:10 %creates ten seperate approximations and will eventually take the mean of all of them
            Random_Pointsx = rand(1,ceil((x_Max-x_Min)*10000))*(x_Max-x_Min)+x_Min;
            Random_Pointsy = rand(1,ceil((x_Max-x_Min)*10000))*(f_Max-f_Min)+f_Min;
            Random_Points = [Random_Pointsx; Random_Pointsy];%generates the random
                     %points within the box containing the section of the function
            hits = 0;
            for i = 1:(x_Max-x_Min)*10000
                if(Random_Points(2,i)< 0)
                    if(Random_Points(2,i) >= F(Random_Points(1,i)))
                    hits = hits -1;%area below y=0 is subtracted
                    end
                else if (Random_Points(2,i) <= F(Random_Points(1,i)))
                    hits = hits + 1;%area above y=0 is added
                    end
                end
            end
            Approximation = [Approximation, hits/(x_Max*10000)*(x_Max-x_Min)*(f_Max-f_Min)];
            %adds current iteration's approximation to the list of k
            %approximations
        end
        Value = mean(Approximation);%takes the mean of  the k approximations
    else
        Value = -1*Approx_Integral(@(x)F(x), x_Max, x_Min);
        %since b<a, switches bounds and multiplies by -1
    end
end