Label the following statements as true or false. (a) The zero vector is a linear combination of any nonempty set of vectors. (b) The span of 0 is 0 . (c) If 5 is a subset of a vector space V, then span(5) equals the intersection of all subspaces of V that contain S. (d) In solving a system of linear equations, it is permissible to multiply an equation by any constant. (e) In solving a system of linear equations, it is permissible to add any multiple of one equation to another. (f) Every system of linear equations has a solution.
Read moreTable of Contents
`6.10
Inner Products and Norms
1.1
Introduction
1.2
Vector Spaces
1.3
Subspaces
1.4
Linear Combinations and Systems of Linear Equations
1.5
Linear Dependence and Linear Independence
1.6
Bases and Dimension
1.7
Maximal Linearly Independent Subsets
2.1
Linear Transformations. Null Spaces, and Ranges
2.2
The Matrix Representation of a Linear Transformation
2.3
Composition of Linear Transformations and Matrix Multiplication
2.4
Invertibility and Isomorphisms
2.5
The Change of Coordinate Matrix
2.6
Dual Spaces
2.7
Homogeneous Linear Differential Equations with Constant Coefficients
3.1
Elementary Matrix Operations and Elementary Matrices
3.2
The Rank of a Matrix and Matrix Inverses
3.3
Systems of Linear Equations Theoretical Aspects
3.4
Systems of Linear Equations Computational Aspects
4.1
Determinants of Order 2
4.2
Determinants of Order n
4.3
Properties of Determinants
4.4
Summary Important Facts about Determinants
4.5
A Characterization of the Determinant
5.1
Eigenvalues and Eigenvectors
5.2
Diagonalizability
5.3
Matrix Limits and Markov Chains
5.4
Invariant Subspaces and the Cayley Hamilton Theorem
6.1
Inner Products and Norms
6.10
Inner Products and Norms
6.11
The Geometry of Orthogonal Operators
6.2
The Gram-Schmidt Orthogonalization Process and Orthogonal Complements
6.3
The Adjoint of a Linear Operator
6.4
Normal and Self-Adjoint. Operators
6.5
Unitary and Orthogonal Operators and Their Matrices
6.6
Orthogonal Projections and the Spectral Theorem
6.7
The Singular Value Decomposition and the Pseudoinverse
6.8
Bilinear and Quadratic Forms
6.9
Einstein As Special Theory of Relativity
7.1
The Jordan Canonical Form I
7.2
The Jordan Canonical Form II
7.3
The Minimal Polynomial
7.4
The Rational Canonical Form
Textbook Solutions for Linear Algebra
Chapter 1.4 Problem 11
Question
Prove that span({x}) = {ax: a F} for any vector x in a vector space. Interpret this result geometrically in R3 .
Solution
Step 1 of 3
To prove that for any vector in a vector space,
Let be an arbitrary element. Then, by definition of linear combination, there exists a scalar
such that
Therefore,
It implies
(i)
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full solution
Title
Linear Algebra 4
Author
Stephen H. Friedberg, Arnold J. Insel, Lawrence E. Spence
ISBN
9780130084514