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Multiply.(2x + 8y)(4x + 8y)

Posted byAnonymous August 20, 2025August 24, 2025

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Multiply.(2x + 8y)(4x + 8y)

Optiоnаl Exаm 1 Definitiоn Retry: D1: Stаte the definitiоn of a linear combination (of matrices). D2: State the definition of a linear transformation. Optional Exam 2 Definition Retry: D3: Complete the following definition: If (S=left{v_{1},v_{2},ldots,v_{k}right}) is a set of vectors in a vector space (V), then (S) is linearly independent if: D4: Complete the following definition: If (S=left{v_{1},v_{2},ldots,v_{k}right}) is a set of vectors in a vector space (V), then (S) is a basis for (V) if:

The use оf mаth tаgs аrоund this nоte triggers MathJax to display the LaTex written on this page as MathML objects. Complete each of the following definitions:  D1.) [4 points] If (A) is a square matrix, then (A) is diagonalizable if: D2.) [6 points] If (V) is a real vector space, then (leftlangle ,rightrangle) is an inner product on (V) if: (there are four properties) 1.) [10 pts] Let (A=begin{bmatrix}3&-2\-1&2end{bmatrix}). Find the eigenvalues of (A), and then find a basis for ONE of the eigenspaces. (Your choice. Do NOT find bases for both, I will only grade the first complete one that you have worked.) 2.) [10 pts] Let (B=begin{bmatrix}6&0&0\1&-3&0\2&5&-1end{bmatrix}). Find the eigenvalues of (B), and then find a basis for any ONE of the eigenspaces. (Your choice. Do NOT find bases for all, I will only grade the first complete one that you have worked.) 3.) [6 pts each] Let (overrightarrow{u}=begin{bmatrix}2\1\-2end{bmatrix}) and (overrightarrow{v}=begin{bmatrix}-1\5\-4end{bmatrix}) be vectors in (mathbb{R}^{3}), with weighted Euclidean inner product corresponding to the weights (w_{1}=1), (w_{2}=2), and (w_{3}=4). Find each of the following. a.) The angle (theta) between (overrightarrow{u}) and (overrightarrow{v}), to the nearest tenth of a degree. b.) (text{proj}_{overrightarrow{v}}overrightarrow{u}). 4.) [6 pts] Using (overrightarrow{a}=begin{bmatrix}2\1\-2end{bmatrix}) and (overrightarrow{b}=begin{bmatrix}-1\5\-4end{bmatrix}), but now with inner product corresponding to the matrix (A=begin{bmatrix}1&0&-1\0&-1&2\1&-1&1end{bmatrix}), find the inner product (leftlangleoverrightarrow{a},overrightarrow{b}rightrangle). 5.) [6 pts each] Let (f=1+x) and (g=1+3x^{2}).  a.) Treating (g) as an element of (P_{2}), find (leftVert grightVert), using the evaluation inner product, with test points (x_{0}=0), (x_{1}=1), and (x_{2}=-1). b.) Treating (f) and (g) as elements of (Cleft[0,1right]), find (leftlangle f,grightrangle), using the integral inner product on (Cleft[0,1right]). 6.) [6 pts] Let (A=begin{bmatrix}1&-5&2\-1&5&1end{bmatrix}) and (B=begin{bmatrix}-1&0&3\2&4&3end{bmatrix}) be elements of (M_{2,3}) with its standard inner product. Find (leftlangle A,Brightrangle). 7.) [10 pts] Let (W) be the subspace of (mathbb{R}^{4}) with the following basis. [left{begin{bmatrix}-1\0\0\2end{bmatrix},begin{bmatrix}1\1\2\0end{bmatrix},begin{bmatrix}1\2\-1\1end{bmatrix}right}] Use the Gram-Schmidt process to convert this to an orthogonal basis for (W). (Hint: If you clear fractions while going through the orthogonalization process, as shown in our examples, it makes things easier.) You are to use the standard inner product (i.e. the dot product) here. 8.) [10 pts] Let (W) be the subspace of (mathbb{R}^{4}) with the following orthogonal basis. [left{begin{bmatrix}2\-1\2\-1end{bmatrix},begin{bmatrix}1\3\3\5end{bmatrix}right}] Let (overrightarrow{v}=begin{bmatrix}1\-1\0\-4end{bmatrix}). Find the projection (text{proj}_{W}overrightarrow{v}). 9.) Consider the inconsistent linear system [begin{align}2x+y&=5\x-2y&=0\x-2y&=3\-x+y&=3end{align}] a.) [6 pts] Find the associated normal system. This should be written in the form of a system of linear equations, not in matrix form. b.) [4 pts] Find the least squares solution. c.) [4 pts] Find the least squares error. EXTRA CREDIT. [5 points] If (W) is a subspace of (mathbb{R}^{n}) whose basis vectors are placed as columns into the matrix (A), what is the matrix (P_{W}) that projects vectors into (W)? That is, what is the formula, in terms of (A), for the matrix (P_{W}) that has the property: [P_{W}overrightarrow{v} = text{proj}_{W}overrightarrow{v}]  

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