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Answer key to introduclinear algebra,tion to linear algebra 6th ed. by strangA foundational text in linear algebra emphasizing both theory and applications. Covers vectors, matrices, rank, linear transformations, eigenvalues, eigenvectors, singular value

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Introduction to Linear Algebra (6th Edition) by Gilbert Strang is a comprehensive and accessible guide to both theoretical and applied linear algebra. Designed for undergraduate students, the book emphasizes understanding the relationships among vectors, matrices, and linear transformations while connecting these concepts to real-world applications in engineering, data science, and computational mathematics. ( ) The text begins with vector spaces and their properties, introducing the concepts of linear independence, span, basis, and dimension. It progresses to matrix operations, including multiplication, inverses, determinants, and rank. Strang uniquely emphasizes the four fundamental subspaces of a matrix—column space, row space, nullspace, and left nullspace—showing how they connect to linear systems and practical applications. Students learn about linear transformations, matrix decompositions such as LU, QR, and singular value decomposition (SVD), and eigenvalue/eigenvector analysis. Each topic is carefully explained with numerous examples, illustrating both geometric intuition and algebraic computation. Exercises range from basic calculations to conceptual challenges, reinforcing understanding and problem-solving skills. The sixth edition incorporates updated examples, contemporary applications, and a stronger focus on computational approaches. Students gain hands-on exposure to applied linear algebra, including signal processing, data analysis, and machine learning foundations. Online resources complement the book, featuring video lectures from MIT OpenCourseWare, downloadable exercises, and solutions for self-study. ( ) For instructors, the text provides a clear structure for lecture planning, with chapters progressing logically from basic theory to advanced applications. For students, it serves both as a classroom textbook and a reference for independent learning, bridging conceptual understanding with practical problem-solving techniques. In summary, Introduction to Linear Algebra (6th Edition) equips learners with a strong foundation in linear algebra theory, methods, and applications. By combining intuitive explanations, rigorous treatment, and computational tools, it prepares students to tackle linear algebra challenges in mathematics, engineering, computer science, and data-driven fields. This edition continues Strang’s legacy of providing a clear, student-centered approach to understanding one of the most essential areas of mathematics.

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ALL 10 CHAPTERS COVERED

,@gmail.com2 nuchojulie 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 ( 1 , 1 , 1 ).
2 2 2
Centers of faces are ( 1 , 1 , 0), ( 1 , 1 , 1) and (0, 1 , 1 ), (1, 1 , 1 ) and ( 1 , 0, 1 ), ( 1 , 1, 1 ).
2 2 2 2 2 2 2 2 2 2 2
2

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 π , sin π ) = ( 3/2, 1/2).
6 6

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

1 3
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.
17 All vectors cv + cw are on the line passing through (0, 0) and u = 1 v+ 1 w. That
2 2

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.
20 (a) 1 u+ 1 v+ 1 w is the center of the triangle between u, v and w; 1 u+ 1 w lies
3 3 3 2 2

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

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.

, @gmail.com4 nuchojulie 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 = c = 3/4
−c +2d −e = 0 2e then d = 2/4
−d +2e = 0 c = 3e e = 1/4
then 4e
=1
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