Difference between revisions of "031 Review Part 2"
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<div class="noautonum">__TOC__</div> | <div class="noautonum">__TOC__</div> | ||
− | == [[ | + | == [[031_Review Part 2,_Problem_1|<span class="biglink"><span style="font-size:80%"> Problem 1 </span></span>]]== |
<span class="exam">Consider the matrix <math style="vertical-align: -31px">A= | <span class="exam">Consider the matrix <math style="vertical-align: -31px">A= | ||
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− | == [[ | + | == [[031_Review Part 2,_Problem_2|<span class="biglink"><span style="font-size:80%"> Problem 2 </span>]] == |
<span class="exam"> Find the dimension of the subspace spanned by the given vectors. Are these vectors linearly independent? | <span class="exam"> Find the dimension of the subspace spanned by the given vectors. Are these vectors linearly independent? | ||
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− | == [[ | + | == [[031_Review Part 2,_Problem_3|<span class="biglink"><span style="font-size:80%"> Problem 3 </span>]] == |
<span class="exam">Let | <span class="exam">Let | ||
<math>B= | <math>B= | ||
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<span class="exam">(b) Define a linear transformation <math style="vertical-align: 0px">T</math> by the formula <math style="vertical-align: -5px">T(\vec{x})=B\vec{x}.</math> Is <math style="vertical-align: 0px">T</math> onto? Explain. | <span class="exam">(b) Define a linear transformation <math style="vertical-align: 0px">T</math> by the formula <math style="vertical-align: -5px">T(\vec{x})=B\vec{x}.</math> Is <math style="vertical-align: 0px">T</math> onto? Explain. | ||
− | == [[ | + | == [[031_Review Part 2,_Problem_4|<span class="biglink"><span style="font-size:80%"> Problem 4 </span>]] == |
<span class="exam"> Suppose <math style="vertical-align: 0px">T</math> is a linear transformation given by the formula | <span class="exam"> Suppose <math style="vertical-align: 0px">T</math> is a linear transformation given by the formula | ||
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− | == [[ | + | == [[031_Review Part 2,_Problem_5|<span class="biglink"><span style="font-size:80%"> Problem 5 </span>]] == |
<span class="exam">Let <math style="vertical-align: 0px">A</math> and <math style="vertical-align: 0px">B</math> be <math style="vertical-align: 0px">6\times 6</math> matrices with <math style="vertical-align: -1px">\text{det }A=-10</math> and <math style="vertical-align: 0px">\text{det }B=5.</math> Use properties of determinants to compute: | <span class="exam">Let <math style="vertical-align: 0px">A</math> and <math style="vertical-align: 0px">B</math> be <math style="vertical-align: 0px">6\times 6</math> matrices with <math style="vertical-align: -1px">\text{det }A=-10</math> and <math style="vertical-align: 0px">\text{det }B=5.</math> Use properties of determinants to compute: | ||
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− | == [[ | + | == [[031_Review Part 2,_Problem_6|<span class="biglink"><span style="font-size:80%"> Problem 6 </span>]] == |
<span class="exam"> Let <math>\vec{v}=\begin{bmatrix} | <span class="exam"> Let <math>\vec{v}=\begin{bmatrix} | ||
-1 \\ | -1 \\ | ||
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<span class="exam">(c) Let <math style="vertical-align: -5px">L=\text{Span }\{\vec{v}\}.</math> Compute the orthogonal projection of <math style="vertical-align: -3px">\vec{y}</math> onto <math style="vertical-align: 0px">L.</math> | <span class="exam">(c) Let <math style="vertical-align: -5px">L=\text{Span }\{\vec{v}\}.</math> Compute the orthogonal projection of <math style="vertical-align: -3px">\vec{y}</math> onto <math style="vertical-align: 0px">L.</math> | ||
− | == [[ | + | == [[031_Review Part 2,_Problem_7|<span class="biglink"><span style="font-size:80%"> Problem 7 </span>]] == |
<span class="exam">(a) Let <math style="vertical-align: -2px">T:\mathbb{R}^2\rightarrow \mathbb{R}^2</math> be a transformation given by | <span class="exam">(a) Let <math style="vertical-align: -2px">T:\mathbb{R}^2\rightarrow \mathbb{R}^2</math> be a transformation given by | ||
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\end{bmatrix}.</math> Find <math style="vertical-align: -4px">AB,~BA^T</math> and <math style="vertical-align: 0px">A-B^T.</math> | \end{bmatrix}.</math> Find <math style="vertical-align: -4px">AB,~BA^T</math> and <math style="vertical-align: 0px">A-B^T.</math> | ||
− | == [[ | + | == [[031_Review Part 2,_Problem_8|<span class="biglink"><span style="font-size:80%"> Problem 8 </span>]] == |
<span class="exam">Let <math style="vertical-align: -31px">A= | <span class="exam">Let <math style="vertical-align: -31px">A= | ||
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\end{bmatrix}.</math> Find <math style="vertical-align: 0px">A^{-1}</math> if possible. | \end{bmatrix}.</math> Find <math style="vertical-align: 0px">A^{-1}</math> if possible. | ||
− | == [[ | + | == [[031_Review Part 2,_Problem_9|<span class="biglink"><span style="font-size:80%"> Problem 9 </span>]] == |
<span class="exam">If <math style="vertical-align: 0px">A</math> is an <math style="vertical-align: 0px">n\times n</math> matrix such that <math style="vertical-align: -4px">AA^T=I,</math> what are the possible values of <math style="vertical-align: 0px">\text{det }A?</math> | <span class="exam">If <math style="vertical-align: 0px">A</math> is an <math style="vertical-align: 0px">n\times n</math> matrix such that <math style="vertical-align: -4px">AA^T=I,</math> what are the possible values of <math style="vertical-align: 0px">\text{det }A?</math> | ||
− | == [[ | + | == [[031_Review Part 2,_Problem_10|<span class="biglink"><span style="font-size:80%"> Problem 10 </span>]] == |
<span class="exam">(a) Suppose a <math style="vertical-align: 0px">6\times 8</math> matrix <math style="vertical-align: 0px">A</math> has 4 pivot columns. What is <math style="vertical-align: -1px">\text{dim Nul }A?</math> Is <math style="vertical-align: -1px">\text{Col }A=\mathbb{R}^4?</math> Why or why not? | <span class="exam">(a) Suppose a <math style="vertical-align: 0px">6\times 8</math> matrix <math style="vertical-align: 0px">A</math> has 4 pivot columns. What is <math style="vertical-align: -1px">\text{dim Nul }A?</math> Is <math style="vertical-align: -1px">\text{Col }A=\mathbb{R}^4?</math> Why or why not? | ||
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<span class="exam">(b) If <math style="vertical-align: 0px">A</math> is a <math style="vertical-align: 0px">7\times 5</math> matrix, what is the smallest possible dimension of <math style="vertical-align: -1px">\text{Nul }A?</math> | <span class="exam">(b) If <math style="vertical-align: 0px">A</math> is a <math style="vertical-align: 0px">7\times 5</math> matrix, what is the smallest possible dimension of <math style="vertical-align: -1px">\text{Nul }A?</math> | ||
− | == [[ | + | == [[031_Review Part 2,_Problem_11|<span class="biglink"><span style="font-size:80%"> Problem 11 </span>]] == |
<span class="exam">Consider the following system of equations. | <span class="exam">Consider the following system of equations. |
Revision as of 18:48, 9 October 2017
This is a sample, and is meant to represent the material usually covered in Math 9C for the final. An actual test may or may not be similar.
Click on the boxed problem numbers to go to a solution.
Problem 1
Consider the matrix and assume that it is row equivalent to the matrix
(a) List rank and
(b) Find bases for and Find an example of a nonzero vector that belongs to as well as an example of a nonzero vector that belongs to
Problem 2
Find the dimension of the subspace spanned by the given vectors. Are these vectors linearly independent?
Problem 3
Let
(a) Is invertible? Explain.
(b) Define a linear transformation by the formula Is onto? Explain.
Problem 4
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.
Problem 5
Let and be matrices with and Use properties of determinants to compute:
(a)
(b)
Problem 6
Let and
(a) Find a unit vector in the direction of
(b) Find the distance between and
(c) Let Compute the orthogonal projection of onto
Problem 7
(a) Let be a transformation given by
Determine whether is a linear transformation. Explain.
(b) Let and Find and
Problem 8
Let Find if possible.
Problem 9
If is an matrix such that what are the possible values of
Problem 10
(a) Suppose a matrix has 4 pivot columns. What is Is Why or why not?
(b) If is a matrix, what is the smallest possible dimension of
Problem 11
Consider the following system of equations.
Find all real values of such that the system has only one solution.