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This is the Solved Exam of Linear Algebra which includes Matrix, System, Row Reduce, System, Solve, Top Left Entry, Appropriate Algorithm, Jump, Last Column etc. Key important points are: Encouraged, Vectors, System, Method, Factorization, Square Matrices, Throughout, Invertible, Symmetric, Reflection Matrix
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Answer Key for Exam #
and
have lengths^
12 + 1^2 + 1^2 + 1^2 = 2 and
respectively, and their dot product is 1 + 1 + 0 + 1 = 3. So the angle θ between them satisfies cos θ =
. Therefore θ = π 6 , or 30◦.
The last step wasn’t necessary since the system was already triangular, but it doesn’t hurt. The second equation gives x 3 = 4 and the third one says x 2 = 2. Then the first equation becomes x 1 + 2 + 8 = 3, so x 1 = −7.
by row operations. Using the first pivot to eliminate the other entries in the first column of A we have
Multiplying the second row by −1 to make the second pivot equal 1, and then using it to clear out the other entries in the second column, we get
To put off the fractions as long as possible we can multiply the first and second rows by 18:
If we now add 7 times the third row to the first, and subtract 5 times the third row from the second, we get
Therefore A−^1 =
4(a) Step 1: subtract twice the first row of A from the second, and thrice the first row from the third. Step 2: subtract 4 times the second row from the third:
Step 1 puts a 2 and 3 respectively in the second and third rows of the first column of L, and step 2 puts a 4
in the middle of the bottom row of L, so L =
(^) and A = LU.
4(b) We may now solve A~x =
(^) in two steps. First we solve L~c = ~b, which in this case is
c 1 c 2 c 3
and we get c 1 = 7; 14 + c 2 = 13, so c 2 = −1; and 21 − 4 + c 3 = 15 so c 3 = −2. Finally we solve U~x = ~c, which in this case is (^)
x 1 x 2 x 3
Here we have x 3 = −2; x 2 − 4 = −1 so x 2 = 3; x 1 + 12 − 6 = 7 so x 1 = 1.
4(c) Here we have to reduce [L I] to
by row operations, which takes three easy steps:
So L−^1 =
, and by symmetry U −^1 =
4(d) Since A = LU and L and U are both invertible, we have A−^1 = U −^1 L−^1. Therefore
if A =
(^) then A−^1 =
5(i) A large family of examples is
( ra rb sa sb
ub vb −ua −va
and
ub vb −ua −va
ra rb sa sb
= (ru + sv)
ab b^2 −a^2 −ab
which is not O unless ru + sv = 0 or a and b are both 0. A specific example is
( 12 20 9 15
but
5(ii) If A is invertible then apply A−^1 to AB = O on the left to get A−^1 AB = A−^1 O, which simplifies to B = O. But if B = O, then BA = OA = O. Similarly, if B is invertible then apply B−^1 to AB = O on the right to get ABB−^1 = OB−^1 , which simplifies to A = O. If A = O, then BA = BO = O. So if either A or B is invertible, then AB = O implies BA = O (and conversely).
5(iii) If we transpose the equation AB = O we get (remember that the order switches) BT^ AT^ = OT^. But OT^ = O, so this says BT^ AT^ = O. If A and B are symmetric then this becomes BA = O.