By Jim Hefferon

ISBN-10: 1440473471

ISBN-13: 9781440473470

The insurance is ordinary: linear structures and Gauss' technique, vector areas, linear maps and matrices, determinants, and eigenvectors and eigenvalues. necessities: A semester of calculus. scholars with 3 semesters of calculus can bypass a number of sections. functions: each one bankruptcy has 3 or 4 discussions of extra issues and functions. those are compatible for self sustaining learn or for small staff paintings. What makes it diverse? The procedure is developmental. even though the presentation is concentrated on protecting the considered necessary fabric via proving issues, it doesn't commence with an assumption that scholars are already capable at summary paintings. as an alternative, it proceeds with loads of motivation, many computational examples, and routines that variety from regimen verifications to (a few) demanding situations. The aim is, within the context of constructing the standard fabric of an undergraduate linear algebra direction, to aid elevate the extent of mathematical adulthood of the category.

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**Additional resources for Linear algebra - answers**

**Example text**

X1 y1 + x2 y2 0 0 = r x y = 0 0 The set R2 is closed under these operations. But it is not a vector space. 18 For each of these, when the subset is independent it must be proved, and when the subset is dependent an example of a dependence must be given. Answers to Exercises 49 (a) It is dependent. Considering 1 2 4 0 c1 −3 + c2 2 + c3 −4 = 0 5 4 14 0 gives rise to this linear system. c1 + 2c2 + 4c3 = 0 −3c1 + 2c2 − 4c3 = 0 5c1 + 4c2 + 14c3 = 0 Gauss’ method 1 −3 5 2 4 2 −4 4 14 0 3ρ1 +ρ2 0 −→ −5ρ1 +ρ3 0 (3/4)ρ2 +ρ3 −→ 1 2 4 0 8 8 0 0 0 0 0 0 yields a free variable, so there are infinitely many solutions.

The first containment [[S]] ⊇ [S] is an instance of the more general, and obvious, fact that for any subset T of a vector space, [T ] ⊇ T . For the other containment, that [[S]] ⊆ [S], take m vectors from [S], namely c1,1 s1,1 +· · ·+c1,n1 s1,n1 , . . , c1,m s1,m + · · · + c1,nm s1,nm , and note that any linear combination of those r1 (c1,1 s1,1 + · · · + c1,n1 s1,n1 ) + · · · + rm (c1,m s1,m + · · · + c1,nm s1,nm ) is a linear combination of elements of S = (r1 c1,1 )s1,1 + · · · + (r1 c1,n1 )s1,n1 + · · · + (rm c1,m )s1,m + · · · + (rm c1,nm )s1,nm and so is in [S].

But this set is all of R. 32 Item (1) is checked in the text. Item (2) has five conditions. First, for closure, if c ∈ R and s ∈ S then c · s ∈ S as c · s = c · s + 0 · 0. Second, because the operations in S are inherited from V , for c, d ∈ R and s ∈ S, the scalar product (c + d) · s in S equals the product (c + d) · s in V , and that equals c · s + d · s in V , which equals c · s + d · s in S. The check for the third, fourth, and fifth conditions are similar to the second conditions’s check just given.

### Linear algebra - answers by Jim Hefferon

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