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Solutions to Exercises for Introduction to Linear Algebra, 6th Edition by (Strang, 2023) | All 10 Chapters Covered

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Download the official Answer Key to Introduction to Linear Algebra, 6th Edition by Gilbert Strang. This complete solutions guide provides step-by-step answers to all exercises in the textbook, ideal for students, tutors, and independent learners studying linear equations, vector spaces, eigenvalues, and matrix theory. Perfect for exam prep, homework support, and mastering core linear algebra concepts. Available in instant PDF format. linear algebra solutions, gilbert strang answer key, introduction to linear algebra pdf, linear algebra 6th edition answers, strang textbook key, linear algebra homework help, math solutions manual, college algebra answers, matrix solutions, eigenvalue step by step, linear systems solved, pdf answer key download, textbook solutions pdf, linear algebra help, math textbook companion, #LinearAlgebra, #GilbertStrang, #Strang6thEdition, #AnswerKeyPDF, #MathSolutions, #AlgebraHelp, #MatrixTheory, #CollegeMath, #TextbookAnswers, #StudyGuide, #StepByStepSolutions, #LinearEquations, #AlgebraSolutions, #StrangAnswers, #PDFDownload, #MathTutoring

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Answer key

,2 Solutions to Exercises

Problem Set 1.1, page 8

1 The combinations give (a) a line in R3 (b) a plane in R3 (c) all of R3 .

2 v + w = (2, 3) and v − w = (6, −1) will be the diagonals of the parallelogram with

v and w as two sides going out from (0, 0).

3 This problem gives the diagonals v + w and v − w of the parallelogram and asks for

the sides: The opposite of Problem 2. In this example v = (3, 3) and w = (2, −2).

4 3v + w = (7, 5) and cv + dw = (2c + d, c + 2d).

5 u+v = (−2, 3, 1) and u+v+w = (0, 0, 0) and 2u+2v+w = ( add first answers) =

(−2, 3, 1). The vectors u, v, w are in the same plane because a combination gives
(0, 0, 0). Stated another way: u = −v − w is in the plane of v and w.

6 The components of every cv + dw add to zero because the components of v and of w

add to zero. c = 3 and d = 9 give (3, 3, −6). There is no solution to cv+dw = (3, 3, 6)
because 3 + 3 + 6 is not zero.

7 The nine combinations c(2, 1) + d(0, 1) with c = 0, 1, 2 and d = (0, 1, 2) will lie on a

lattice. If we took all whole numbers c and d, the lattice would lie over the whole plane.

8 The other diagonal is v − w (or else w − v). Adding diagonals gives 2v (or 2w).

9 The fourth corner can be (4, 4) or (4, 0) or (−2, 2). Three possible parallelograms!

10 i − j = (1, 1, 0) is in the base (x-y plane). i + j + k = (1, 1, 1) is the opposite corner

from (0, 0, 0). Points in the cube have 0 ≤ x ≤ 1, 0 ≤ y ≤ 1, 0 ≤ z ≤ 1.

11 Four more corners (1, 1, 0), (1, 0, 1), (0, 1, 1), (1, 1, 1). The center point is ( 12 , 12 , 12 ).

Centers of faces are ( 12 , 12 , 0), ( 12 , 12 , 1) and (0, 12 , 12 ), (1, 12 , 12 ) and ( 12 , 0, 12 ), ( 12 , 1, 12 ).

12 The combinations of i = (1, 0, 0) and i + j = (1, 1, 0) fill the xy plane in xyz space.

13 Sum = zero vector. Sum = −2:00 vector = 8:00 vector. 2:00 is 30◦ from horizontal

= (cos π6 , sin π6 ) = ( 3/2, 1/2).

14 Moving the origin to 6:00 adds j = (0, 1) to every vector. So the sum of twelve vectors

changes from 0 to 12j = (0, 12).

,Solutions to Exercises 3

3 1
15 The point v + w is three-fourths of the way to v starting from w. The vector
4 4
1 1 1 1
v + w is halfway to u = v + w. The vector v + w is 2u (the far corner of the
4 4 2 2
parallelogram).

16 All combinations with c + d = 1 are on the line that passes through v and w.

The point V = −v + 2w is on that line but it is beyond w.
1
17 All vectors cv + cw are on the line passing through (0, 0) and u = 2v + 12 w. That
line continues out beyond v + w and back beyond (0, 0). With c ≥ 0, half of this line
is removed, leaving a ray that starts at (0, 0).

18 The combinations cv + dw with 0 ≤ c ≤ 1 and 0 ≤ d ≤ 1 fill the parallelogram with

sides v and w. For example, if v = (1, 0) and w = (0, 1) then cv + dw fills the unit
square. But when v = (a, 0) and w = (b, 0) these combinations only fill a segment of
a line.

19 With c ≥ 0 and d ≥ 0 we get the infinite “cone” or “wedge” between v and w. For

example, if v = (1, 0) and w = (0, 1), then the cone is the whole quadrant x ≥ 0, y ≥
0. Question: What if w = −v? The cone opens to a half-space. But the combinations
of v = (1, 0) and w = (−1, 0) only fill a line.
1
20 (a) 3u + 13 v + 13 w is the center of the triangle between u, v and w; 12 u + 12 w lies
between u and w (b) To fill the triangle keep c ≥ 0, d ≥ 0, e ≥ 0, and c + d + e = 1.

21 The sum is (v − u) + (w − v) + (u − w) = zero vector. Those three sides of a triangle

are in the same plane!

22 The vector 12 (u + v + w) is outside the pyramid because c + d + e = 1
2
+ 1
2
+ 1
2
> 1.

23 All vectors are combinations of u, v, w as drawn (not in the same plane). Start by

seeing that cu + dv fills a plane, then adding ew fills all of R3 .

24 The combinations of u and v fill one plane. The combinations of v and w fill another

plane. Those planes meet in a line: only the vectors cv are in both planes.

25 (a) For a line, choose u = v = w = any nonzero vector (b) For a plane, choose
u and v in different directions. A combination like w = u + v is in the same plane.

,4 Solutions to Exercises

26 Two equations come from the two components: c + 3d = 14 and 2c + d = 8. The

solution is c = 2 and d = 4. Then 2(1, 2) + 4(3, 1) = (14, 8).

27 A four-dimensional cube has 24 = 16 corners and 2 · 4 = 8 three-dimensional faces

and 24 two-dimensional faces and 32 edges in Worked Example 2.4 A.

28 There are 6 unknown numbers v1 , v2 , v3 , w1 , w2 , w3 . The six equations come from the

components of v + w = (4, 5, 6) and v − w = (2, 5, 8). Add to find 2v = (6, 10, 14)
so v = (3, 5, 7) and w = (1, 0, −1).

29 Fact : For any three vectors u, v, w in the plane, some combination cu + dv + ew is

the zero vector (beyond the obvious c = d = e = 0). So if there is one combination
Cu + Dv + Ew that produces b, there will be many more—just add c, d, e or 2c, 2d, 2e
to the particular solution C, D, E.

The example has 3u − 2v + w = 3(1, 3) − 2(2, 7) + 1(1, 5) = (0, 0). It also has
−2u + 1v + 0w = b = (0, 1). Adding gives u − v + w = (0, 1). In this case c, d, e
equal 3, −2, 1 and C, D, E = −2, 1, 0.

Could another example have u, v, w that could NOT combine to produce b ? Yes. The
vectors (1, 1), (2, 2), (3, 3) are on a line and no combination produces b. We can easily
solve cu + dv + ew = 0 but not Cu + Dv + Ew = b.

30 The combinations of v and w fill the plane unless v and w lie on the same line through

(0, 0). Four vectors whose combinations fill 4-dimensional space: one example is the
“standard basis” (1, 0, 0, 0), (0, 1, 0, 0), (0, 0, 1, 0), and (0, 0, 0, 1).

31 The equations cu + dv + ew = b are


2c −d =1 So d = 2e c = 3/4
−c +2d −e = 0 then c = 3e d = 2/4
−d +2e = 0 then 4e = 1 e = 1/4

,Solutions to Exercises 5

Problem Set 1.2, page 18

1 u · v = −2.4 + 2.4 = 0, u · w = −.6 + 1.6 = 1, u · (v + w) = u · v + u · w =

0 + 1, w · v = 4 + 6 = 10 = v · w.

2 kuk = 1 and kvk = 5 and kwk = 5. Then |u · v| = 0 < (1)(5) and |v · w| = 10 <

5 5, confirming the Schwarz inequality.

3 Unit vectors v/kvk = ( 45 , 35 ) = (0.8, 0.6). The vectors w, (2, −1), and −w make
√ √
0 ◦ , 90 ◦ , 180 ◦ angles with w and w/kwk = (1/ 5, 2/ 5). The cosine of θ is kv
vk ·
w = 10/5 5. √
kw k

4 (a) v · (−v) = −1 (b) (v + w) · (v − w) = v · v + w · v − v · w − w · w =
1+( )−( )−1 = 0 so θ = 90◦ (notice v·w = w·v) (c) (v−2w)·(v+2w) =
v · v − 4w · w = 1 − 4 = −3.
√ √
5 u1 = v/kvk = (1, 3)/ 10 and u2 = w/kwk = (2, 1, 2)/3. U 1 = (3, −1)/ 10 is
√ √
perpendicular to u1 (and so is (−3, 1)/ 10). U 2 could be (1, −2, 0)/ 5: There is a
whole plane of vectors perpendicular to u2 , and a whole circle of unit vectors in that
plane.

6 All vectors w = (c, 2c) are perpendicular to v. They lie on a line. All vectors (x, y, z)

with x + y + z = 0 lie on a plane. All vectors perpendicular to (1, 1, 1) and (1, 2, 3)
lie on a line in 3-dimensional space.

7 (a) cos θ = v · w/kvkkwk = 1/(2)(1) so θ = 60◦ or π/3 radians (b) cos θ =
0 so θ = 90 or π/2 radians (c) cos θ = 2/(2)(2) = 1/2 so θ = 60◦ or π/3



(d) cos θ = −1/ 2 so θ = 135◦ or 3π/4.

8 (a) False: v and w are any vectors in the plane perpendicular to u (b) True: u ·
(v + 2w) = u · v + 2u · w = 0 (c) True, ku − vk2 = (u − v) · (u − v) splits into
u · u + v · v = 2 when u · v = v · u = 0.

9 If v2 w2 /v1 w1 = −1 then v2 w2 = −v1 w1 or v1 w1 + v2 w2 = v · w = 0: perpendicular!

The vectors (1, 4) and (1, − 14 ) are perpendicular.

,6 Solutions to Exercises

10 Slopes 2/1 and −1/2 multiply to give −1: then v · w = 0 and the vectors (the direc-

tions) are perpendicular.

11 v · w < 0 means angle > 90◦ ; these w’s fill half of 3-dimensional space.

12 (1, 1) perpendicular to (1, 5) − c(1, 1) if (1, 1) · (1, 5) − c(1, 1) · (1, 1) = 6 − 2c = 0 or

c = 3; v · (w − cv) = 0 if c = v · w/v · v. Subtracting cv is the key to constructing
a perpendicular vector.

13 The plane perpendicular to (1, 0, 1) contains all vectors (c, d, −c). In that plane, v =

(1, 0, −1) and w = (0, 1, 0) are perpendicular.

14 One possibility among many: u = (1, −1, 0, 0), v = (0, 0, 1, −1), w = (1, 1, −1, −1)

and (1, 1, 1, 1) are perpendicular to each other. “We can rotate those u, v, w in their
3D hyperplane and they will stay perpendicular.”
√ √ √
15 12 (x + y) = (2 + 8)/2 = 5 and 5 > 4; cos θ = 2 16/ 10 10 = 8/10.

16 kvk2 = 1 + 1 + · · · + 1 = 9 so kvk = 3; u = v/3 = ( 13 , . . . , 13 ) is a unit vector in 9D;

w = (1, −1, 0, . . . , 0)/ 2 is a unit vector in the 8D hyperplane perpendicular to v.
√ √
17 cos α = 1/ 2, cos β = 0, cos γ = −1/ 2. For any vector v = (v 1 , v 2 , v 3 ) the

cosines with (1, 0, 0) and (0, 0, 1) are cos2 α+cos2 β+cos2 γ = (v12 +v22 +v32 )/kvk2 = 1.

18 kvk2 = 42 + 22 = 20 and kwk2 = (−1)2 + 22 = 5. Pythagoras is k(3, 4)k2 = 25 =

20 + 5 for the length of the hypotenuse v + w = (3, 4).

19 Start from the rules (1), (2), (3) for v · w = w · v and u · (v + w) and (cv) · w. Use

rule (2) for (v + w) · (v + w) = (v + w) · v + (v + w) · w. By rule (1) this is
v · (v + w) + w · (v + w). Rule (2) again gives v · v + v · w + w · v + w · w =
v · v + 2v · w + w · w. Notice v · w = w · v! The main point is to feel free to open
up parentheses.

20 We know that (v − w) · (v − w) = v · v − 2v · w + w · w. The Law of Cosines writes

kvkkwk cos θ for v · w. Here θ is the angle between v and w. When θ < 90◦ this
v · w is positive, so in this case v · v + w · w is larger than kv − wk2 .

Pythagoras changes from equality a2 +b2 = c2 to inequality when θ < 90 ◦ or θ > 90 ◦ .

,Solutions to Exercises 7

21 2v · w ≤ 2kvkkwk leads to kv + wk2 = v · v + 2v · w + w · w ≤ kvk2 + 2kvkkwk +

kwk2 . This is (kvk + kwk)2 . Taking square roots gives kv + wk ≤ kvk + kwk.

22 v12 w12 + 2v1 w1 v2 w2 + v22 w22 ≤ v12 w12 + v12 w22 + v22 w12 + v22 w22 is true (cancel 4 terms)

because the difference is v12 w22 + v22 w12 − 2v1 w1 v2 w2 which is (v1 w2 − v2 w1 )2 ≥ 0.

23 cos β = w1 /kwk and sin β = w2 /kwk. Then cos(β −a) = cos β cos α+sin β sin α =

v1 w1 /kvkkwk + v2 w2 /kvkkwk = v · w/kvkkwk. This is cos θ because β − α = θ.
1
24 Example 6 gives |u1 ||U1 | ≤ 2
2 (u1 + U12 ) and |u2 ||U2 | ≤ 12 (u22 + U22 ). The whole line
becomes .96 ≤ (.6)(.8) + (.8)(.6) ≤ 12 (.62 + .82 ) + 12 (.82 + .62 ) = 1. True: .96 < 1.
p
25 The cosine of θ is x/ x2 + y 2 , near side over hypotenuse. Then | cos θ|2 is not greater

than 1: x2 /(x2 + y 2 ) ≤ 1.
26–27 (with apologies for that typo !) These two lines add to 2||v||2 + 2||w||2 :

||v + w||2 = (v + w) · (v + w) = v · v + v · w + w · v + w · w

||v − w||2 = (v − w) · (v − w) = v · v − v · w − w · v + w · w
28 The vectors w = (x, y) with (1, 2) · w = x + 2y = 5 lie on a line in the xy plane. The

shortest w on that line is (1, 2). (The Schwarz inequality kwk ≥ v · w/kvk = 5 is

an equality when cos θ = 0 and w = (1, 2) and kwk = 5.)

29 The length kv − wk is between 2 and 8 (triangle inequality when kvk = 5 and kwk =

3). The dot product v · w is between −15 and 15 by the Schwarz inequality.

30 Three vectors in the plane could make angles greater than 90◦ with each other: for

example (1, 0), (−1, 4), (−1, −4). Four vectors could not do this (360◦ total angle).
How many can do this in R3 or Rn ? Ben Harris and Greg Marks showed me that the
answer is n + 1. The vectors from the center of a regular simplex in Rn to its n + 1
vertices all have negative dot products. If n+2 vectors in Rn had negative dot products,
project them onto the plane orthogonal to the last one. Now you have n + 1 vectors in
Rn−1 with negative dot products. Keep going to 4 vectors in R2 : no way!

31 For a specific example, pick v = (1, 2, −3) and then w = (−3, 1, 2). In this example
√ √
cos θ = v · w/kvkkwk = −7/ 14 14 = −1/2 and θ = 120◦ . This always
happens when x + y + z = 0:

,8 Solutions to Exercises

1 1
v · w = xz + xy + yz = (x + y + z)2 − (x2 + y 2 + z 2 )
2 2
1 1
This is the same as v · w = 0 − kvkkwk. Then cos θ = .
2 2


32 Wikipedia gives this proof of geometric mean G = 3 xyz ≤ arithmetic mean
A = (x + y + z)/3. First there is equality in case x = y = z. Otherwise A is
somewhere between the three positive numbers, say for example z < A < y.

Use the known inequality g ≤ a for the two positive numbers x and y + z − A. Their
1 1
mean a = 2 (x + y + z − A) is 2 (3A − A) = same as A! So a ≥ g says that
A3 ≥ g 2 A = x(y + z − A)A. But (y + z − A)A = (y − A)(A − z) + yz > yz.
Substitute to find A3 > xyz = G3 as we wanted to prove. Not easy!

There are many proofs of G = (x1 x2 · · · xn )1/n ≤ A = (x1 + x2 + · · · + xn )/n. In
calculus you are maximizing G on the plane x1 + x2 + · · · + xn = n. The maximum
occurs when all x’s are equal.

1
33 The columns of the 4 by 4 “Hadamard matrix” (times 2
) are perpendicular unit
vectors:
 
1 1 1 1
 
1 −1 1 −1
 
1 1  
H=  .
2 2 1
 
1 −1 −1 
 
1 −1 −1 1


34 The commands V = randn (3, 30); D = sqrt (diag (V ′ ∗ V )); U = V \D; will give

30 random unit vectors in the columns of U . Then u ′ ∗ U is a row matrix of 30 dot
products whose average absolute value should be close to 2/π.




Problem Set 1.3, page 29
1 3s1 + 4s2 + 5s3 = (3, 7, 12). The same vector b comes from S times x = (3, 4, 5):

,Solutions to Exercises 9


      
1 0 0 3 (row 1) · x 3
      
1 1 0   4  =  (row 2) · x  =  7  .
      
      
1 1 1 5 (row 2) · x 12

2 The solutions are y1 = 1, y2 = 0, y3 = 0 (right side = column 1) and y1 = 1, y2 = 3,

y3 = 5. That second example illustrates that the first n odd numbers add to n2 .
  
y1 = B1 y1 = B 1 1 0 0 B
  1
3 y1 + y2 = B2 gives y2 = −B1 +B2 = −1 1 0   B2 
  
  
y1 + y2 + y3 = B 3 y3 = −B2 +B3 0 −1 1 B3
   
1 0 0 1 0 0
   
The inverse of S =  1 1 0  is A = −1 1 0 : independent columns in A and S!
   
   
1 1 1 0 −1 1

4 The combination 0w 1 + 0w2 + 0w 3 always gives the zero vector, but this problem

looks for other zero combinations (then the vectors are dependent, they lie in a plane):
w2 = (w1 + w 3 )/2 so one combination that gives zero is w 1 − 2w2 + w3 = 0.

5 The rows of the 3 by 3 matrix in Problem 4 must also be dependent: r 2 = 12 (r 1 + r 3 ).

The column and row combinations that produce 0 are the same: this is unusual. Two
solutions to y1 r 1 + y2 r 2 + y3 r 3 = 0 are (Y1 , Y2 , Y3 ) = (1, −2, 1) and (2, −4, 2).
 
1 1 0
 
6 c=3  3 2 1  has column 3 = column 1 − column 2
 
 
7 4 3
 
1 0 −1
 
c = −1  1 1 0  has column 3 = − column 1 + column 2
 
 
0 1 1
 
0 0 0
 
c=0  2 1 5  has column 3 = 3 (column 1) − column 2
 
 
3 3 6

, 10 Solutions to Exercises

7 All three rows are perpendicular to the solution x (the three equations r 1 · x = 0 and

r 2 ·x = 0 and r 3 ·x = 0 tell us this). Then the whole plane of the rows is perpendicular
to x (the plane is also perpendicular to all multiples cx).
  
x1 − 0 = b 1 x1 = b 1 1 0 0 0 b1
  
x2 − x1 = b 2 x2 = b 1 + b 2 1 1 0 0   b2 
  
8 =    = A−1 b
x3 − x2 = b 3 x3 = b 1 + b 2 + b 3 1 1 1 0   b3 
  
  
x4 − x3 = b 4 x4 = b 1 + b 2 + b 3 + b 4 1 1 1 1 b4

9 The cyclic difference matrix C has a line of solutions (in 4 dimensions) to Cx = 0:

  
   
1 0 0 −1 x1 0 c
      
 −1 1 0 0   x2   0  c
      
    =   when x =   = any constant vector.
      
 0 −1 1 0   x3   0  c
      
0 0 −1 1 x4 0 c

   
z2 − z1 = b 1 z1 = −b1 − b2 − b3 −1 −1 −1 b1
   
10 z3 − z2 = b 2 z2 = − b2 − b3 =  0 −1 −1   b2  = ∆−1 b
   
   
0 − z3 = b 3 z3 = − b3 0 0 −1 b3

11 The forward differences of the squares are (t + 1)2 − t2 = t2 + 2t + 1 − t2 = 2t + 1.

Differences of the nth power are (t + 1)n − tn = tn − tn + ntn−1 + · · · . The leading
term is the derivative ntn−1 . The binomial theorem gives all the terms of (t + 1)n .


12 Centered difference matrices of even size seem to be invertible. Look at eqns. 1 and 4:

        
0 1 0 0 x1 b1 First x1 −b2 − b4
        
 −1 0 1 0   x2   b2  solve  x2   b1
        

   =    = 
        
 0 −1 0 1   x3   b 3  x2 = b 1  x3   −b4 
        
0 0 −1 0 x4 b4 −x3 = b4 x4 b1 + b3


13 Odd size: The five centered difference equations lead to b1 + b3 + b5 = 0.

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