The variance formula is easily extended to multiple variables if you use a little matrix algebra. Say SD is an nX1 standard deviation vector, SD' is the transpose and P is the nXn correlation matrix. Just multiply SD' X P X SD (in this case, you'll want the weights multiplied to the corresponding entries in the SD vectors before you start).

i agree with the .03974 and .19935.

I also got the same answers for both variance and SD of the portfolio.

There is a Quiz Question in the textbook designed specifically for a 3-stock portfolio.  In the sixth edition it is problem #8.  It shows you the nine boxes you need to sum.

Got the same answers, thanks for checking!

for part B in hw, I was trying to following the formula. Can someone tell me where i did wrong?

Vp = (x1)^2 * V1 + (x2)^2 * V2+ (x3)^2 * V3+ 2*x1*x2*Cov(1,2) + 2*x1*x3*Cov(1,3) + 2*x2*x3*Cov(2,3)

Vp = (0.5)^2 * 0.2^2 + (0.3)^2* 0.3^2 + (0.2)^2 *0.4^2+ 2*0.5*0.3*0.5 + 2*0.5*0.2*0.3 + 2*0.3*0.2*0.1=0.2465