LESSON 2: Vector and Matrix Equations

Terminology:
column vector, scalar, zero vector, linear combination, span, matrix, matrix equation, matrix-vector product, identity matrix.
Objectives:
learn about column vectors and their algebraic properties; understand what a linear combination is; understand what the span of a set of vectors is; learn how to multiply a vector by a matrix; understand the connections between matrix-vector equations and linear systems; understand the algebraic properties of matrix-vector products.
Reading Assignment:
Chapter 1, Sections 1.3-1.4 (pages 27-46).
Lesson Outline
Key Ideas and Discussion:
A (column) vector in n dimensions (in tex2html_wrap_inline64) is a column of n real numbers. Vectors can be multiplied by scalars, and added together. The algebraic properties for vectors are similar to the properties satisfied by scalars. A linear combination of vectors is a sum of scalar multiples of the vectors. A linear system is just a vector equation where the left-hand side of the equation is a linear combination of some vectors with the unknowns for the system used as scalar multipliers. The right-hand side of the equation is a vector of right-hand sides for the linear system. The set of all possible linear combinations of a set of vectors is called the span of the set. In two (three) dimensions the span can interpreted geometrically as a line (plane). In general, the span of a set of n-vectors is a subset of tex2html_wrap_inline64; sometimes the span includes all of tex2html_wrap_inline64 and sometimes it does not.

The result of multiplying an n-vector tex2html_wrap_inline76 by an tex2html_wrap_inline78 matrix A is an m-vector tex2html_wrap_inline84 (tex2html_wrap_inline86) that is a linear combination (with the tex2html_wrap_inline88's as multipliers) of the columns of A. The matrix equation tex2html_wrap_inline92 is another way of writing down a linear system whose coefficient matrix is A and right-hand side is tex2html_wrap_inline96. When we try to solve a linear system, we are trying to find scalars tex2html_wrap_inline88 so that if we use these scalars as multipliers for the columns of A and add the results together, then we get tex2html_wrap_inline96. Another way to consider this process is to say that we are trying to determine if tex2html_wrap_inline96 is in the span of the columns of A. The columns of A span tex2html_wrap_inline110 if and only if tex2html_wrap_inline92 has a solution for all possible tex2html_wrap_inline96's in tex2html_wrap_inline110.

Practice Problems:
1.3.3, 5, 9, 11, 19, 25 (pp. 36-37); 1.4.3, 5, 9, 15, 27, 29 (pp. 46-47).

Assignment



Alan C Genz
Fri Jul 24 14:13:29 PDT 1998