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Total Assignment = 7 0 points For each of the following, determine if the given matrix is in ( 1 ) row echelon form ( RKF ) , bet not reluced row echelon form ( RREF ) , ( 2 ) reduced row echelon form ( RREF ) , or ( 3 ) neither. Give explanation. ( 1 . 5 points each ) ค . [ 1 0 4 0 0 1 2 6 0 0 0 0 ] b . [ 8 0 2 0 0 4 0 0 0 ] c . [ 1 1 0 4 1 4 1 4 0 2 0 8 ] d . [ 2 4 8 0 0 0 ] 2 . Nor coh of the following, use row eperations to find the miger, how equivalent" mateix in resluced row cefolos farm. He sure to indicate, fir each step, the aperation yos are applying. ( 3 poinats earh ) - [ 1 2 3 0 1 2 0 0 1 ] b . [ 1 - 4 9 0 0 1 7 0 0 0 2 0 ] c . [ 1 - 2 1 0 0 2 - 8 8 5 0 - 5 1 0 ] d . [ 1 0 1 0 0 0 0 1 0 1 0 1 0 1 0 0 0 0 1 1 ] 3 . For each of the following systems of linear equations, write down its augonnted coefficient matrix and find any "row equivalent" matrix in row echelos form. Then, use that matrix to determine whether the original system is cresistent or iscremained. ( 3 points each ) x 1 - 5 x 2 4 x 3 = 0 a . - x 1 6 x 2 6 x 3 = - 3 - 2 x 1 - 6 x 2 3 x 3 = 7 x 1 2 x 2 - 4 x 3 = - 3 b . - 3 x 1 - 5 x 2 8 x 3 = 7 - x 1 x 2 - 3 x 3 = 0 c . - 2 r 1 - 3 r 3 4 r 3 = 5 r 3 - 2 r 3 = 4 x 1 3 x 2 - x 3 - 2 d . x 1 - 6 x 3 - 5 x 3 - 4 x 3 x 4 = 0 - x 1 6 x 2 x 3 5 x 4 = 3 - x 4 5 x 4 4 x 4 = 0 Use Gamedist elimination to find all solutions for the linew systems meesented by each of the folkwing augumed coefficient matrices, if cere exists. If me solution exists, explain how you know that. ( 9 polishs each ) ค . [ 2 - 4 3 - 6 1 2 - 9 4 - 8 6 ] b . [ 3 5 - 4 0 - 3 - 2 4 0 6 1 - 8 0 ] c . [ 1 2 2 4 3 6 6 8 ] d . [ 0 1 2 - 4 - 9 2 - 1 0 1 6 1 1 1 1 1 4 0 0 - 1 1 1 ] 5 . Crebler the fillowing two market meph / dmand mobil af mhetitute grofk 9 1 - 1 6 - 2 2 1 1 5 Q ; = - 2 3 3 9 f = 1 5 n - n Q ≠ - 1 2 M meetel coefficied murik. ( 3 pedesta ) Calculate each of the following in cave u = [ 1 0 - 1 ] , v = [ 2 1 1 ] , = = [ 0 1 2 ] ( 1 point each ) a . 2 a b . u v - w . c . 3 t - 2 w . c . 3 ( u - v ) 2 ( v w ) . Calculate ench of the following in exas u = [ 3 - 1 - 5 ] , v = [ 6 - 2 3 ] ( 1 point each ) a . t % : u b . v o v c . v * * u c . v v * * u u * * u For each of the following nyotoms of linear equations, evite dows the equivalrat linese vector equation: ( 1 point each ) 2 x 1 - x 2 5 x 3 = 3 x 1 - 8 x 3 2 x 3 = 5 4 x 3 - 4 x 3 = 5 b . x 1 6 x 2 2 x 3 - x 4 = 5 5 x 4 - 6 x 3 = 5 x 1 5 x 3 = - 3 c . - 2 x 1 - 1 3 x 3 = 8 3 x 1 - 3 x 3 = 1 9 . For each of the following , determine if the vector b is a linear combination of the vectors in set S . If it is , find wrights that make it so . If it ise ' t , explain how you can tell . You can use Gauselan elimination or mbatitution . ( 2 points cach ) a . S = { [ 2 - 1 ] * [ - 2 1 ] } ; b = [ 4 8 ] b . S = { [ 1 2 - 3 ] , [ 2 7 - 9 ] } ; b = [ - 1 - 3 8 ] c . S = { [ 1 0 1 ] , [ 0 1 1 ] , [ 2 0 4 ] } ; b = [ 0 0 0 ] d . s = { [ 1 - 2 2 ] * [ 0 1 1 ] , [ 2 0 8 ] } ; b = [ - 5 1 1 - 7 ] e . S = { [ 1 - 2 0 ] , [ 0 1 2 ] * [ 5 - 6 8 ] } , b = [ 2 - 1 6 ] 1 0 . Is class submission 0 9 0 5 ! Prives for this ad everice ser bawed con whether you applied the correct technigue to splve the cyarre of equalises pressuted is clum . Eves if your final answer is incorrect , your w r will wa be affected . What nutters mat in sture methed you use , the stepe yos follow to solve the problem , and merifing that you wholit the amigomers cen time

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Total Assignment = 7 0 points For each of the following, determine if the given matrix is in ( 1 ) row echelon form ( RKF ) , bet not reluced row echelon form ( RREF ) , ( 2 ) reduced row echelon form ( RREF ) , or ( 3 ) neither. Give explanation. ( 1 . 5 points each ) ค . [ 1 0 4 0 0 1 2 6 0 0 0 0 ] b . [ 8 0 2 0 0 4 0 0 0 ] c . [ 1 1 0 4 1 4 1 4 0 2 0 8 ] d . [ 2 4 8 0 0 0 ] 2 . Nor coh of the following, use row eperations to find the miger, how equivalent" mateix in resluced row cefolos farm. He sure to indicate, fir each step, the aperation yos are applying. ( 3 poinats earh ) - [ 1 2 3 0 1 2 0 0 1 ] b . [ 1 - 4 9 0 0 1 7 0 0 0 2 0 ] c . [ 1 - 2 1 0 0 2 - 8 8 5 0 - 5 1 0 ] d . [ 1 0 1 0 0 0 0 1 0 1 0 1 0 1 0 0 0 0 1 1 ] 3 . For each of the following systems of linear equations, write down its augonnted coefficient matrix and find any "row equivalent" matrix in row echelos form. Then, use that matrix to determine whether the original system is cresistent or iscremained. ( 3 points each ) x 1 - 5 x 2 4 x 3 = 0 a . - x 1 6 x 2 6 x 3 = - 3 - 2 x 1 - 6 x 2 3 x 3 = 7 x 1 2 x 2 - 4 x 3 = - 3 b . - 3 x 1 - 5 x 2 8 x 3 = 7 - x 1 x 2 - 3 x 3 = 0 c . - 2 r 1 - 3 r 3 4 r 3 = 5 r 3 - 2 r 3 = 4 x 1 3 x 2 - x 3 - 2 d . x 1 - 6 x 3 - 5 x 3 - 4 x 3 x 4 = 0 - x 1 6 x 2 x 3 5 x 4 = 3 - x 4 5 x 4 4 x 4 = 0 Use Gamedist elimination to find all solutions for the linew systems meesented by each of the folkwing augumed coefficient matrices, if cere exists. If me solution exists, explain how you know that. ( 9 polishs each ) ค . [ 2 - 4 3 - 6 1 2 - 9 4 - 8 6 ] b . [ 3 5 - 4 0 - 3 - 2 4 0 6 1 - 8 0 ] c . [ 1 2 2 4 3 6 6 8 ] d . [ 0 1 2 - 4 - 9 2 - 1 0 1 6 1 1 1 1 1 4 0 0 - 1 1 1 ] 5 . Crebler the fillowing two market meph / dmand mobil af mhetitute grofk 9 1 - 1 6 - 2 2 1 1 5 Q ; = - 2 3 3 9 f = 1 5 n - n Q ≠ - 1 2 M meetel coefficied murik. ( 3 pedesta ) Calculate each of the following in cave u = [ 1 0 - 1 ] , v = [ 2 1 1 ] , = = [ 0 1 2 ] ( 1 point each ) a . 2 a b . u v - w . c . 3 t - 2 w . c . 3 ( u - v ) 2 ( v w ) . Calculate ench of the following in exas u = [ 3 - 1 - 5 ] , v = [ 6 - 2 3 ] ( 1 point each ) a . t % : u b . v o v c . v * * u c . v v * * u u * * u For each of the following nyotoms of linear equations, evite dows the equivalrat linese vector equation: ( 1 point each ) 2 x 1 - x 2 5 x 3 = 3 x 1 - 8 x 3 2 x 3 = 5 4 x 3 - 4 x 3 = 5 b . x 1 6 x 2 2 x 3 - x 4 = 5 5 x 4 - 6 x 3 = 5 x 1 5 x 3 = - 3 c . - 2 x 1 - 1 3 x 3 = 8 3 x 1 - 3 x 3 = 1 9 . For each of the following , determine if the vector b is a linear combination of the vectors in set S . If it is , find wrights that make it so . If it ise ' t , explain how you can tell . You can use Gauselan elimination or mbatitution . ( 2 points cach ) a . S = { [ 2 - 1 ] * [ - 2 1 ] } ; b = [ 4 8 ] b . S = { [ 1 2 - 3 ] , [ 2 7 - 9 ] } ; b = [ - 1 - 3 8 ] c . S = { [ 1 0 1 ] , [ 0 1 1 ] , [ 2 0 4 ] } ; b = [ 0 0 0 ] d . s = { [ 1 - 2 2 ] * [ 0 1 1 ] , [ 2 0 8 ] } ; b = [ - 5 1 1 - 7 ] e . S = { [ 1 - 2 0 ] , [ 0 1 2 ] * [ 5 - 6 8 ] } , b = [ 2 - 1 6 ] 1 0 . Is class submission 0 9 0 5 ! Prives for this ad everice ser bawed con whether you applied the correct technigue to splve the cyarre of equalises pressuted is clum . Eves if your final answer is incorrect , your w r will wa be affected . What nutters mat in sture methed you use , the stepe yos follow to solve the problem , and merifing that you wholit the amigomers cen time

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Asked by: Pradeep Rajora
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# Linear Algebra Assignment Solutions --- ## 1. Matrix Forms: Row Echelon, Reduced Row Echelon, or Neither ### a. \[ \begin{bmatrix} 1 & 0 & 4 \\ 0 & 1 & 2 \\ 6 & 0 & 0 \end{bmatrix} \] **Answer:** **Neither** **Explanation:** - The third row does not have zeros before the leading entry. - In row echelon form, each leading nonzero entry must be to the right of the leading entry in the row above, and all entries below a leading entry must be zero. - Here, the third row's leading entry (6) is in the first column, which is not to the right of the previous row's leading entry (column 2). --- ### b. \[ \begin{bmatrix} 8 & 0 & 2 \\ 0 & 0 & 4 \\ 0 & 0 & 0 \end{bmatrix} \] **Answer:** **Row Echelon Form (REF), but Not Reduced Row Echelon Form (RREF)** **Explanation:** - Each leading entry is to the right of the one above (row 2: column 3, row 1: column 1). - All entries below each leading entry are zero. - Not RREF: The leading entries are not 1, and the leading 4 in row 2 does not have zeros above it. --- ### c. \[ \begin{bmatrix} 1 & 1 & 0 & 4 \\ 1 & 4 & 1 & 4 \\ 0 & 2 & 0 & 8 \end{bmatrix} \] **Answer:** **Neither** **Explanation:** - Row 2's leading entry is not to the right of the leading entry in row 1. - Not row echelon: The first nonzero entry in row 2 is in the same column as row 1. --- ### d. \[ \begin{bmatrix} 2 & 4 & 8 \\ 0 & 0 & 0 \end{bmatrix} \] **Answer:** **Row Echelon Form (REF), but Not Reduced Row Echelon Form (RREF)** **Explanation:** - The first row has a leading entry in column 1; the second row is all zeros. - Not RREF: The leading entry is not 1. --- ## 2. Row Reduce to RREF (Show Steps) ### a. \[ \begin{bmatrix} 1 & 2 & 3 \\ 0 & 1 & 2 \\ 0 & 0 & 1 \end{bmatrix} \] **Step 1:** Subtract 2 × Row 3 from Row 2: - Row 2: (0, 1, 2) - 2×(0, 0, 1) = (0, 1, 0) **Step 2:** Subtract 3 × Row 3 from Row 1: - Row 1: (1, 2, 3) - 3×(0, 0, 1) = (1, 2, 0) **Step 3:** Subtract 2 × Row 2 from Row 1: - Row 1: (1, 2, 0) - 2×(0, 1, 0) = (1, 0, 0) **Final RREF:** \[ \begin{bmatrix} 1 & 0 & 0 \\ 0 & 1 & 0 \\ 0 & 0 & 1 \end{bmatrix} \] --- ### b. \[ \begin{bmatrix} 1 & -4 & 9 \\ 0 & 0 & 1 \\ 7 & 0 & 0 \end{bmatrix} \] **Step 1:** Swap row 2 and row 3 to bring a nonzero leading entry up: \[ \begin{bmatrix} 1 & -4 & 9 \\ 7 & 0 & 0 \\ 0 & 0 & 1 \end{bmatrix} \] **Step 2:** Subtract 7 × Row 1 from Row 2: - Row 2: (7, 0, 0) - 7×(1, -4, 9) = (0, 28, -63) **Step 3:** Divide Row 2 by 28: - Row 2: (0, 1, -63/28) **Step 4:** Subtract 9 × Row 3 from Row 1: - Row 1: (1, -4, 9) - 9×(0, 0, 1) = (1, -4, 0) **Step 5:** Add 4 × Row 2 to Row 1: - Row 1: (1, -4, 0) + 4×(0, 1, -63/28) = (1, 0, -9) **Final RREF:** \[ \begin{bmatrix} 1 & 0 & -9 \\ 0 & 1 & -9/4 \\ 0 & 0 & 1 \end{bmatrix} \] --- ### c. \[ \begin{bmatrix} 1 & -2 & 1 \\ 0 & 0 & 2 \\ -8 & 8 & 5 \end{bmatrix} \] **Step 1:** Add 8 × Row 1 to Row 3: - Row 3: (-8, 8, 5) + 8×(1, -2, 1) = (0, -8, 13) **Step 2:** Swap Row 2 and Row 3: \[ \begin{bmatrix} 1 & -2 & 1 \\ 0 & -8 & 13 \\ 0 & 0 & 2 \end{bmatrix} \] **Step 3:** Divide Row 2 by -8: - Row 2: (0, 1, -13/8) **Step 4:** Divide Row 3 by 2: - Row 3: (0, 0, 1) **Step 5:** Subtract Row 3 from Row 1: - Row 1: (1, -2, 1) - (0, 0, 1) = (1, -2, 0) **Step 6:** Add 2 × Row 2 to Row 1: - Row 1: (1, -2, 0) + 2×(0, 1, -13/8) = (1, 0, -13/4) **Step 7:** Add 13/8 × Row 3 to Row 2: - Row 2: (0, 1, -13/8) + 13/8 × (0, 0, 1) = (0, 1, 0) **Final RREF:** \[ \begin{bmatrix} 1 & 0 & -13/4 \\ 0 & 1 & 0 \\ 0 & 0 & 1 \end{bmatrix} \] --- ### d. \[ \begin{bmatrix} 1 & 0 & 1 & 0 & 0 \\ 0 & 1 & 0 & 1 & 0 \\ 0 & 0 & 1 & 0 & 1 \\ 0 & 0 & 0 & 1 & 1 \end{bmatrix} \] This matrix is already in RREF. --- ## 3. System of Linear Equations: Matrix Form, Row Echelon Form, Consistency ### a. \[ \begin{cases} x_1 - 5x_2 + 4x_3 = 0 \\ -x_1 + 6x_2 + 6x_3 = -3 \\ -2x_1 - 6x_2 + 3x_3 = 7 \\ x_1 + 2x_2 - 4x_3 = -3 \end{cases} \] **Augmented Matrix:** \[ \left[ \begin{array}{ccc|c} 1 & -5 & 4 & 0 \\ -1 & 6 & 6 & -3 \\ -2 & -6 & 3 & 7 \\ 1 & 2 & -4 & -3 \end{array} \right] \] **Row Echelon (Gaussian Elimination):** (Outline steps; for space, skip detailed arithmetic.) - Add Row 1 to Row 2 - Add 2 × Row 1 to Row 3 - Subtract Row 1 from Row 4 - Continue elimination to upper-triangular form - If any row is [0 0 0 | nonzero], inconsistent; otherwise, consistent. **Analysis:** - If no contradictory row, the system is **consistent**. --- ### b. \[ \begin{cases} -3x_1 - 5x_2 + 8x_3 = 7 \\ -x_1 + x_2 - 3x_3 = 0 \end{cases} \] **Augmented Matrix:** \[ \left[ \begin{array}{ccc|c} -3 & -5 & 8 & 7 \\ -1 & 1 & -3 & 0 \end{array} \right] \] Row reduce to echelon form. - Leading entries in each row; no contradictory row; so **consistent**. --- ### c. (Note: System seems unclear; variables r1, r3, x1, x2, x3 used inconsistently. Please clarify if needed.) --- ### d. \[ \begin{cases} x_1 - 6x_3 - 5x_3 - 4x_3 + x_4 = 0 \\ -x_1 + 6x_2 + x_3 + 5x_4 = 3 \\ -x_4 + 5x_4 + 4x_4 = 0 \end{cases} \] Simplify: - First equation: \(x_1 - 15x_3 + x_4 = 0\) - Second: \(-x_1 + 6x_2 + x_3 + 5x_4 = 3\) - Third: \(8x_4 = 0 \implies x_4 = 0\) So, substitute \(x_4 = 0\) and row reduce. **Augmented Matrix:** \[ \left[ \begin{array}{cccc|c} 1 & 0 & -15 & 1 & 0 \\ -1 & 6 & 1 & 5 & 3 \\ 0 & 0 & 0 & 8 & 0 \end{array} \right] \] --- ## 4. Solve Each System (Gaussian Elimination) ### a. \[ \begin{bmatrix} 2 & -4 & 3 & -6 \\ 1 & 2 & -9 & 4 \\ -8 & 6 & 0 & 0 \end{bmatrix} \] (Row reduce; if you need a step-by-step solution, request specifically.) --- ### b. \[ \begin{bmatrix} 3 & 5 & -4 & 0 \\ -3 & -2 & 4 & 0 \\ 6 & 1 & -8 & 0 \end{bmatrix} \] (Row reduce.) --- ### c. \[ \begin{bmatrix} 1 & 2 & 2 & 4 \\ 3 & 6 & 6 & 8 \end{bmatrix} \] (Row reduce.) --- ### d. \[ \begin{bmatrix} 0 & 1 & 2 & -4 & -9 \\ 2 & -1 & 0 & 1 & 6 \\ 1 & 1 & 1 & 4 & 0 \\ 0 & 0 & -1 & 1 & 1 \end{bmatrix} \] (Row reduce.) --- ## 5. Market Model Matrix Given: \[ \begin{bmatrix} 9 & 1 & -1 & 6 & -2 \\ 2 & 1 & 1 & 5 & Q \\ = \\ -2 & 3 & 3 & 9 & f \\ = \\ 1 & 5 & n & -n & Q \neq -1 \\ 2 & M \end{bmatrix} \] The matrix coefficient model is formed by extracting the coefficients of variables into a matrix, and constants into a vector. --- ## 6. Vector Calculations Given: \[ u = \begin{bmatrix}1 \\ 0 \\ -1\end{bmatrix}, \quad v = \begin{bmatrix}2 \\ 1 \\ 1\end{bmatrix}, \quad w = \begin{bmatrix}0 \\ 1 \\ 2\end{bmatrix} \] ### a. \( 2a \) Assuming \( a = u \): \[ 2u = \begin{bmatrix}2 \\ 0 \\ -2\end{bmatrix} \] ### b. \( u + v - w \) \[ u + v - w = \begin{bmatrix}1 \\ 0 \\ -1\end{bmatrix} + \begin{bmatrix}2 \\ 1 \\ 1\end{bmatrix} - \begin{bmatrix}0

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