Page 36 - Linear Algebra Done Right
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Chapter 2. Finite-Dimensional Vector Spaces
                       22
                                              Span and Linear Independence
                                                A linear combination of a list (v 1 ,...,v m ) of vectors in V is a vector
                                              of the form
                                              2.1                   a 1 v 1 +· · ·+ a m v m ,
                                              where a 1 ,...,a m ∈ F. The set of all linear combinations of (v 1 ,...,v m )
                        Some mathematicians   is called the span of (v 1 ,...,v m ), denoted span(v 1 ,...,v m ). In other
                          use the term linear  words,
                       span, which means the
                               same as span.       span(v 1 ,...,v m ) ={a 1 v 1 + ··· + a m v m : a 1 ,...,a m ∈ F}.
                                                                                                 3
                                                As an example of these concepts, suppose V = F . The vector

                                              (7, 2, 9) is a linear combination of (2, 1, 3), (1, 0, 1) because
                                                                (7, 2, 9) = 2(2, 1, 3) + 3(1, 0, 1).

                                              Thus (7, 2, 9) ∈ span (2, 1, 3), (1, 0, 1) .
                                                You should verify that the span of any list of vectors in V is a sub-
                                              space of V. To be consistent, we declare that the span of the empty list
                                              () equals {0} (recall that the empty set is not a subspace of V).
                                                If (v 1 ,...,v m ) is a list of vectors in V, then each v j is a linear com-
                                              bination of (v 1 ,...,v m ) (to show this, set a j = 1 and let the other a’s
                                              in 2.1 equal 0). Thus span(v 1 ,...,v m ) contains each v j . Conversely,
                                              because subspaces are closed under scalar multiplication and addition,
                                              every subspace of V containing each v j must contain span(v 1 ,...,v m ).
                                              Thus the span of a list of vectors in V is the smallest subspace of V
                                              containing all the vectors in the list.
                                                If span(v 1 ,...,v m ) equals V, we say that (v 1 ,...,v m ) spans V.A
                               Recall that by  vector space is called finite dimensional if some list of vectors in it
                                                                           n
                       definition every list has  spans the space. For example, F is finite dimensional because
                                finite length.
                                                           (1, 0,..., 0), (0, 1, 0,..., 0),...,(0,..., 0, 1)

                                                     n
                                              spans F , as you should verify.
                                                Before giving the next example of a finite-dimensional vector space,
                                              we need to define the degree of a polynomial. A polynomial p ∈P(F)
                                              is said to have degree m if there exist scalars a 0 ,a 1 ,...,a m ∈ F with
                                              a m  = 0 such that

                                              2.2              p(z) = a 0 + a 1 z + ··· + a m z m
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