Difference between revisions of "031 Review Problems"
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− | '''21.''' | + | '''21.''' Let <math>A= |
+ | \begin{bmatrix} | ||
+ | 1 & 3 & 8 \\ | ||
+ | 2 & 4 &11\\ | ||
+ | 1 & 2 & 5 | ||
+ | \end{bmatrix}.</math> Find <math>A^{-1}</math> if possible. | ||
+ | |||
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!Solution: | !Solution: | ||
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− | '''22.''' | + | '''22.''' Find a formula for <math>\begin{bmatrix} |
+ | 1 & -6 \\ | ||
+ | 2 & -6 | ||
+ | \end{bmatrix}^k</math> by diagonalizing the matrix. | ||
+ | |||
{| class="mw-collapsible mw-collapsed" style = "text-align:left;" | {| class="mw-collapsible mw-collapsed" style = "text-align:left;" | ||
!Solution: | !Solution: | ||
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'''23.''' | '''23.''' | ||
+ | |||
+ | (a) Show that if <math>\vec{x}</math> is an eigenvector of the matrix <math>A</math> corresponding to the eigenvalue 2, then <math>\vec{x}</math> is an eigenvector of <math>A^3-A^2+I.</math> What is the corresponding eigenvalue? | ||
+ | |||
+ | (b) Show that if <math>\vec{y}</math> is an eigenvector of the matrix <math>A</math> corresponding to the eigenvalue 3 and <math>A</math> is invertible, then <math>\vec{y}</math> is an eigenvector of <math>A^{-1}.</math> What is the corresponding eigenvalue? | ||
+ | |||
{| class="mw-collapsible mw-collapsed" style = "text-align:left;" | {| class="mw-collapsible mw-collapsed" style = "text-align:left;" | ||
!Solution: | !Solution: | ||
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− | '''24.''' | + | '''24.''' Let <math>A=\begin{bmatrix} |
+ | 3 & 0 & -1 \\ | ||
+ | 0 & 1 &-3\\ | ||
+ | 1 & 0 & 0 | ||
+ | \end{bmatrix}\begin{bmatrix} | ||
+ | 3 & 0 & 0 \\ | ||
+ | 0 & 4 &0\\ | ||
+ | 0 & 0 & 3 | ||
+ | \end{bmatrix}\begin{bmatrix} | ||
+ | 0 & 0 & 1 \\ | ||
+ | -3 & 1 &9\\ | ||
+ | -1 & 0 & 3 | ||
+ | \end{bmatrix}.</math> | ||
+ | |||
+ | Use the Diagonalization Theorem to find the eigenvalues of <math>A</math> and a basis for each eigenspace. | ||
+ | |||
{| class="mw-collapsible mw-collapsed" style = "text-align:left;" | {| class="mw-collapsible mw-collapsed" style = "text-align:left;" | ||
!Solution: | !Solution: | ||
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|} | |} | ||
− | '''25.''' | + | '''25.''' Give an example of a <math>3\times 3</math> matrix <math>A</math> with eigenvalues 5,-1 and 3. |
+ | |||
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!Solution: | !Solution: | ||
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− | '''26.''' | + | '''26.''' Assume <math>A^2=I.</math> Find Nul <math>A.</math> |
+ | |||
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!Solution: | !Solution: | ||
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|} | |} | ||
− | '''27.''' | + | '''27.''' If <math>A</math> is an <math>n\times n</math> matrix such that <math>AA^T=I,</math> what are the possible values of det <math>A?</math> |
+ | |||
{| class="mw-collapsible mw-collapsed" style = "text-align:left;" | {| class="mw-collapsible mw-collapsed" style = "text-align:left;" | ||
!Solution: | !Solution: | ||
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|} | |} | ||
− | '''28.''' | + | '''28.''' Show that if <math>\vec{x}</math> is an eigenvector of the matrix product <math>AB</math> and <math>B\vec{x}\ne \vec{0},</math> then <math>B\vec{x}</math> is an eigenvector of <math>BA.</math> |
+ | |||
{| class="mw-collapsible mw-collapsed" style = "text-align:left;" | {| class="mw-collapsible mw-collapsed" style = "text-align:left;" | ||
!Solution: | !Solution: | ||
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'''29.''' | '''29.''' | ||
+ | |||
+ | (a) Suppose a <math>6\times 8</math> matrix <math>A</math> has 4 pivot columns. What is dim Nul <math>A?</math> Is Col <math>A=\mathbb{R}^4?</math> Why or why not? | ||
+ | |||
+ | (b) If <math>A</math> is a <math>7\times 5</math> matrix, what is the smallest possible dimension of Nul <math>A?</math> | ||
+ | |||
{| class="mw-collapsible mw-collapsed" style = "text-align:left;" | {| class="mw-collapsible mw-collapsed" style = "text-align:left;" | ||
!Solution: | !Solution: | ||
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− | '''30.''' | + | '''30.''' Consider the following system of equations. |
+ | |||
+ | <math>x_1+kx_2=1</math> | ||
+ | |||
+ | <math>3x_1+5x_2=2k</math> | ||
+ | |||
+ | Find all real values of <math>k</math> such that the system has only one solution. | ||
+ | |||
{| class="mw-collapsible mw-collapsed" style = "text-align:left;" | {| class="mw-collapsible mw-collapsed" style = "text-align:left;" | ||
!Solution: | !Solution: | ||
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− | '''31.''' | + | '''31.''' Suppose <math>\{\vec{u},\vec{v}\}</math> is a basis of the eigenspace corresponding to the eigenvalue 0 of a <math>5\times 5</math> matrix <math>A.</math> |
+ | |||
+ | (a) Is <math>\vec{w}=\vec{u}-2\vec{v}</math> an eigenvector of <math>A?</math> If so, find the corresponding eigenvalue. | ||
+ | |||
+ | If not, explain why. | ||
+ | |||
+ | (b) Find the dimension of Col <math>A.</math> | ||
+ | |||
{| class="mw-collapsible mw-collapsed" style = "text-align:left;" | {| class="mw-collapsible mw-collapsed" style = "text-align:left;" | ||
!Solution: | !Solution: |
Revision as of 18:13, 24 August 2017
This is a list of sample problems and is meant to represent the material usually covered in Math 31. An actual test may or may not be similar.
1. True or false: If all the entries of a matrix are then det must be
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2. True or false: If a matrix is diagonalizable, then the matrix must be diagonalizable as well.
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3. True or false: If is a matrix with characteristic equation then is diagonalizable.
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4. True or false: If is invertible, then is diagonalizable.
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5. True or false: If and are invertible matrices, then so is
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6. True or false: If is a matrix and dim Nul then is consistent for all in
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7. True or false: Let for matrices and If is invertible, then is invertible.
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8. True or false: Let be a subspace of and be a vector in If and then
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9. True or false: If is an invertible matrix, and and are matrices such that then
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10.
(a) Is the matrix diagonalizable? If so, explain why and diagonalize it. If not, explain why not.
(b) Is the matrix diagonalizable? If so, explain why and diagonalize it. If not, explain why not.
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11. Find the eigenvalues and eigenvectors of the matrix
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12. Consider the matrix and assume that it is row equivalent to the matrix
(a) List rank and dim Nul
(b) Find bases for Col and Nul Find an example of a nonzero vector that belongs to Col as well as an example of a nonzero vector that belongs to Nul
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13. Find the dimension of the subspace spanned by the given vectors. Are these vectors linearly independent?
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14. Let
(a) Is invertible? Explain.
(b) Define a linear transformation by the formula Is onto? Explain.
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15. Suppose is a linear transformation given by the formula
(a) Find the standard matrix for
(b) Let Find
(c) Is in the range of Explain.
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16. Let and be matrices with det and det Use properties of
determinants to compute:
(a) det
(b) det
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17. Let
(a) Find a basis for the eigenspace(s) of
(b) Is the matrix diagonalizable? Explain.
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18. Let and
(a) Find a unit vector in the direction of
(b) Find the distance between and
(c) Let Span Compute the orthogonal projection of onto
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19. Let Span Is in Explain.
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20.
(a) Let be a transformation given by
Determine whether is a linear transformation. Explain.
(b) Let and Find and
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21. Let Find if possible.
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22. Find a formula for by diagonalizing the matrix.
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23.
(a) Show that if is an eigenvector of the matrix corresponding to the eigenvalue 2, then is an eigenvector of What is the corresponding eigenvalue?
(b) Show that if is an eigenvector of the matrix corresponding to the eigenvalue 3 and is invertible, then is an eigenvector of What is the corresponding eigenvalue?
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24. Let
Use the Diagonalization Theorem to find the eigenvalues of and a basis for each eigenspace.
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25. Give an example of a matrix with eigenvalues 5,-1 and 3.
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26. Assume Find Nul
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27. If is an matrix such that what are the possible values of det
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28. Show that if is an eigenvector of the matrix product and then is an eigenvector of
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29.
(a) Suppose a matrix has 4 pivot columns. What is dim Nul Is Col Why or why not?
(b) If is a matrix, what is the smallest possible dimension of Nul
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30. Consider the following system of equations.
Find all real values of such that the system has only one solution.
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31. Suppose is a basis of the eigenspace corresponding to the eigenvalue 0 of a matrix
(a) Is an eigenvector of If so, find the corresponding eigenvalue.
If not, explain why.
(b) Find the dimension of Col
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