Given that the standard deviation of a group of data X1 x2 X3 is 2, then the standard deviation of data 2x1 + 3,2x2 + 3,2x3 + 3D is fast!

Given that the standard deviation of a group of data X1 x2 X3 is 2, then the standard deviation of data 2x1 + 3,2x2 + 3,2x3 + 3D is fast!


Variance of the first set of data var (x) = 2 ^ 2 = 4
The variance of the second group of data var (2x + 3) = 2 ^ 2 * var (x) = 16, standard deviation = root 16 = 4
Formula var (AX + b) = a ^ 2 * var (x)



It is known that the n-dimensional vectors A1, A2, A3, A4, A5 are linearly independent and a is an invertible matrix of order n. It is proved that Aa1, aa2, aa3, AA4, aa5 are linear


Because (Aa1, aa2, aa3, AA4, aa5) = a (A1, A2, A3, A4, A5)
And a is reversible
So r (Aa1, aa2, aa3, AA4, aa5) = R [a (A1, A2, A3, A4, A5)] = R (A1, A2, A3, A4, A5) = 5
So Aa1, aa2, aa3, AA4, aa5 are linearly independent



Let a and B be n-dimensional column vectors, then the rank of n-order matrix C = AB ^ t is R (a) =, why not equal to N, and the answer is 0 or 1


Let a = (A1, A2,. An) ^ t, B = (B1, B2,. BN) ^ t
Then AB ^ t = A1B1, A1B2, a1b3. A1bn
a2b1 a2b2 a2b3 .a2bn
..
anb1 anb2 anb3 .anbn
Note any 2 * 2 submatrix AiBj aibk
asbj asbk
Its determinant is 0, so any k (greater than or equal to 2) level subexpression is equal to 0
So the rank of AB ^ t



Let a be your cubic matrix, A1 and A2 be the eigenvectors of a which belong to the eigenvalues - 1 and 1 respectively. Let the vector A3 satisfy aa3 = A2 + a3, let P = (A1, A2, A3), and find p-1ap


Known by
AP = A(a1,a2,a3)
= (Aa1,Aa2,Aa3)
= (-a1,a2,a2+a3)
= (a1,a2,a3) B
B=
-1 0 0
0 1 1
0 0 1
So AP = PB
So p ^ - 1AP = B=
-1 0 0
0 1 1
0 0 1