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Appendix G Figures and video examples

0.5 Proof techniques

Figure 0.5.9 Mathematical induction as ladder of propositions

1.1 Systems of linear equations

Figure 1.1.8 Using Sage to visualize \(\mathcal{P}\colon ax+by+cz=d\) via normal vector \(\boldn=(a,b,c)\)

1.3 Solving linear systems

Figure 1.3.7 Video: solving linear systems
Figure 1.3.8 Video: solving linear systems 2
Figure 1.3.10 Decision tree for number of solutions to a system

2.1 Matrix arithmetic

Figure 2.1.18 Visualizing matrix multiplication
Figure 2.1.28 Video: three methods of matrix multiplication

2.2 Matrix algebra

Figure 2.2.12 Video: matrix multiplication is associative
Figure 2.2.13 Video: transpose property

2.4 The invertibility theorem

Figure 2.4.13 Video: inverse algorithm

2.5 The determinant

Figure 2.5.13 Video: determinant

3.1 Real vector spaces

Figure 3.1.6 Visualizing \(\R^n\text{:}\) points and arrows
Figure 3.1.7 Visualizing vector arithmetic

3.2 Linear transformations

Figure 3.2.19 Visualizing reflection and rotation
Figure 3.2.23 Orthogonal projection onto a line
Figure 3.2.27 Orthogonal projection onto plane and normal line
Figure 3.2.30 Video: deciding if \(T\) is linear
Figure 3.2.31 Video: deciding if \(T\) is linear

3.3 Subspaces

Figure 3.3.5 Video: deciding if \(W\subseteq V\) is a subspace
Figure 3.3.6 Video: deciding if \(W\subseteq V\) is a subspace

3.4 Null space and image

Figure 3.4.3 Null space and image
Figure 3.4.(a)
Figure 3.4.(b)
Figure 3.4.(c)

3.5 Span and linear independence

Figure 3.5.4 Video: computing span
Figure 3.5.20 Video: linear independence of functions

3.6 Bases

Figure 3.6.11 Video: deciding if a set is a basis (\(\R^n\))
Figure 3.6.12 Video: deciding if a set is a basis

3.7 Dimension

Figure 3.7.10 Video: computing dimension

3.8 Rank-nullity theorem and fundamental spaces

Figure 3.8.11 Video: computing fundamental spaces
Figure 3.8.14 Video: contracting to a basis

4.1 Coordinate vectors

Figure 4.1.8 Video: coordinate vectors

4.2 Matrix representations of linear transformations

Figure 4.2.8 Commutative diagram for \([T]_B^{B'}\)
Figure 4.2.11 Video: matrix representations

4.3 Change of basis

Figure 4.3.11 Video: change of basis matrix
Figure 4.3.18 Video: change of basis for transformations
Figure 4.3.19 Video: computing reflection via change of basis
Figure 4.3.22 The holy commutative tent of linear algebra

4.4 Eigenvectors and eigenvalues

Figure 4.4.2 Reflection through \(\ell=\Span\{(1,2)\}\)
Figure 4.4.7 Visualizing eigenvectors

4.5 Diagonalization

Figure 4.5.17 Video: deciding if diagonalizable

5.3 Orthogonal projection

Figure 5.3.12 Video: orthogonal projection in function space
Figure 5.3.21 Least-squares visualization

5.4 The spectral theorem

Figure 5.4.14 Eigenspaces of a symmetric matrix are orthogonal