Deck 8: Orthogonality

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Find all values of a so that u and v are orthogonal.
Find all values of a so that u and v are orthogonal.  <div style=padding-top: 35px>
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Find all values of a so that u and v are orthogonal.
Find all values of a so that u and v are orthogonal.  <div style=padding-top: 35px>
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Determine if the vectors form an orthogonal set.
Determine if the vectors form an orthogonal set.  <div style=padding-top: 35px>
Question
Determine if the vectors form an orthogonal set.
Determine if the vectors form an orthogonal set.  <div style=padding-top: 35px>
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Find all values of a (if any) so that the given vectors form an orthogonal set.
Find all values of a (if any) so that the given vectors form an orthogonal set.  <div style=padding-top: 35px>
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Suppose Suppose   and   are orthogonal with   and   . Determine   .<div style=padding-top: 35px> and Suppose   and   are orthogonal with   and   . Determine   .<div style=padding-top: 35px> are orthogonal with Suppose   and   are orthogonal with   and   . Determine   .<div style=padding-top: 35px> and Suppose   and   are orthogonal with   and   . Determine   .<div style=padding-top: 35px> . Determine Suppose   and   are orthogonal with   and   . Determine   .<div style=padding-top: 35px> .
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Determine all values of a so that the vector u is orthogonal to the subspace S.
Determine all values of a so that the vector u is orthogonal to the subspace S.  <div style=padding-top: 35px>
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Find a basis for Find a basis for   for the subspace S.  <div style=padding-top: 35px> for the subspace S.
Find a basis for   for the subspace S.  <div style=padding-top: 35px>
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Find a basis for Find a basis for   for the subspace S.  <div style=padding-top: 35px> for the subspace S.
Find a basis for   for the subspace S.  <div style=padding-top: 35px>
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Suppose S is a subspace of Suppose S is a subspace of   , and   . Determine   .<div style=padding-top: 35px> , and Suppose S is a subspace of   , and   . Determine   .<div style=padding-top: 35px> . Determine Suppose S is a subspace of   , and   . Determine   .<div style=padding-top: 35px> .
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If If   is an orthogonal basis for a subspace S of   , and   then   is a diagonal   matrix.<div style=padding-top: 35px> is an orthogonal basis for a subspace S of If   is an orthogonal basis for a subspace S of   , and   then   is a diagonal   matrix.<div style=padding-top: 35px> , and If   is an orthogonal basis for a subspace S of   , and   then   is a diagonal   matrix.<div style=padding-top: 35px> then If   is an orthogonal basis for a subspace S of   , and   then   is a diagonal   matrix.<div style=padding-top: 35px> is a diagonal If   is an orthogonal basis for a subspace S of   , and   then   is a diagonal   matrix.<div style=padding-top: 35px> matrix.
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If If   is a linearly independent set of vectors, then   is orthogonal.<div style=padding-top: 35px> is a linearly independent set of vectors, then If   is a linearly independent set of vectors, then   is orthogonal.<div style=padding-top: 35px> is orthogonal.
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If If   is an orthogonal set of vectors, and   , then   .<div style=padding-top: 35px> is an orthogonal set of vectors, and If   is an orthogonal set of vectors, and   , then   .<div style=padding-top: 35px> , then
If   is an orthogonal set of vectors, and   , then   .<div style=padding-top: 35px> .
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If A is any matrix, then If A is any matrix, then   .<div style=padding-top: 35px> .
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If S is a subspace of If S is a subspace of   , then   .<div style=padding-top: 35px> , then If S is a subspace of   , then   .<div style=padding-top: 35px> .
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Determine Determine   , where   .<div style=padding-top: 35px> , where Determine   , where   .<div style=padding-top: 35px> .
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Determine Determine   , where   .<div style=padding-top: 35px> , where Determine   , where   .<div style=padding-top: 35px> .
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Determine Determine   , where   ,   .<div style=padding-top: 35px> , where Determine   , where   ,   .<div style=padding-top: 35px> , Determine   , where   ,   .<div style=padding-top: 35px> .
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Find an orthogonal basis for the subspace Find an orthogonal basis for the subspace   .<div style=padding-top: 35px> .
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Find an orthogonal basis for the subspace Find an orthogonal basis for the subspace   .<div style=padding-top: 35px> .
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Find an orthogonal basis for the subspace Find an orthogonal basis for the subspace   .<div style=padding-top: 35px> .
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Find Find   , where   .<div style=padding-top: 35px> , where Find   , where   .<div style=padding-top: 35px> .
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Apply the Gram-Schmidt process to the given basis for Apply the Gram-Schmidt process to the given basis for   to produce an orthogonal basis for   . Then normalize the vectors to produce an orthonormal basis for   .  <div style=padding-top: 35px> to produce an orthogonal basis for Apply the Gram-Schmidt process to the given basis for   to produce an orthogonal basis for   . Then normalize the vectors to produce an orthonormal basis for   .  <div style=padding-top: 35px> . Then normalize the vectors to produce an orthonormal basis for Apply the Gram-Schmidt process to the given basis for   to produce an orthogonal basis for   . Then normalize the vectors to produce an orthonormal basis for   .  <div style=padding-top: 35px> .
Apply the Gram-Schmidt process to the given basis for   to produce an orthogonal basis for   . Then normalize the vectors to produce an orthonormal basis for   .  <div style=padding-top: 35px>
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Find an orthonormal basis for the subspace Find an orthonormal basis for the subspace   .<div style=padding-top: 35px> .
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Find an orthonormal basis for the subspace Find an orthonormal basis for the subspace   , and use it to to find   , where   .<div style=padding-top: 35px> , and use it to to find Find an orthonormal basis for the subspace   , and use it to to find   , where   .<div style=padding-top: 35px> , where Find an orthonormal basis for the subspace   , and use it to to find   , where   .<div style=padding-top: 35px> .
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If S is a nonzero subspace of If S is a nonzero subspace of   , then for every vector u in   ,   belongs to S.<div style=padding-top: 35px> , then for every vector u in If S is a nonzero subspace of   , then for every vector u in   ,   belongs to S.<div style=padding-top: 35px> , If S is a nonzero subspace of   , then for every vector u in   ,   belongs to S.<div style=padding-top: 35px> belongs to S.
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If If   is a nonzero subspace of   , and u belongs to   , then   .<div style=padding-top: 35px> is a nonzero subspace of If   is a nonzero subspace of   , and u belongs to   , then   .<div style=padding-top: 35px> , and u belongs to If   is a nonzero subspace of   , and u belongs to   , then   .<div style=padding-top: 35px> , then If   is a nonzero subspace of   , and u belongs to   , then   .<div style=padding-top: 35px> .
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If If   is a nonzero subspace of   , and u belongs to   , then   for every vector   .<div style=padding-top: 35px> is a nonzero subspace of If   is a nonzero subspace of   , and u belongs to   , then   for every vector   .<div style=padding-top: 35px> , and u belongs to If   is a nonzero subspace of   , and u belongs to   , then   for every vector   .<div style=padding-top: 35px> , then If   is a nonzero subspace of   , and u belongs to   , then   for every vector   .<div style=padding-top: 35px> for every vector If   is a nonzero subspace of   , and u belongs to   , then   for every vector   .<div style=padding-top: 35px> .
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If If   and   are nonzero subspaces of   , then   for every vector u in   .<div style=padding-top: 35px> and If   and   are nonzero subspaces of   , then   for every vector u in   .<div style=padding-top: 35px> are nonzero subspaces of If   and   are nonzero subspaces of   , then   for every vector u in   .<div style=padding-top: 35px> , then If   and   are nonzero subspaces of   , then   for every vector u in   .<div style=padding-top: 35px> for every vector u in If   and   are nonzero subspaces of   , then   for every vector u in   .<div style=padding-top: 35px> .
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If If   is an orthonormal set, then   is linearly independent.<div style=padding-top: 35px> is an orthonormal set, then If   is an orthonormal set, then   is linearly independent.<div style=padding-top: 35px> is linearly independent.
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Determine if the given matrix is symmetric.
Determine if the given matrix is symmetric.  <div style=padding-top: 35px>
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Determine if the given matrix is orthogonal.
Determine if the given matrix is orthogonal.  <div style=padding-top: 35px>
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The eigenvalues and corresponding eigenvectors for a symmetric matrix A are given. Find matrices D and P of an orthogonal diagonalization of A. The eigenvalues and corresponding eigenvectors for a symmetric matrix A are given. Find matrices D and P of an orthogonal diagonalization of A.  <div style=padding-top: 35px>
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The eigenvalues and corresponding eigenvectors for a symmetric matrix A are given. Find matrices D and P of an orthogonal diagonalization of A. The eigenvalues and corresponding eigenvectors for a symmetric matrix A are given. Find matrices D and P of an orthogonal diagonalization of A.  <div style=padding-top: 35px>
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The eigenvalues for the symmetric matrix A are given. Find matrices D and P of an orthogonal diagonalization of A. The eigenvalues for the symmetric matrix A are given. Find matrices D and P of an orthogonal diagonalization of A.  <div style=padding-top: 35px>
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The eigenvalues for the symmetric matrix A are given. Find matrices D and P of an orthogonal diagonalization of A. The eigenvalues for the symmetric matrix A are given. Find matrices D and P of an orthogonal diagonalization of A.  <div style=padding-top: 35px>
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Verify that the eigenvalues of Verify that the eigenvalues of   are nonnegative.  <div style=padding-top: 35px> are nonnegative.
Verify that the eigenvalues of   are nonnegative.  <div style=padding-top: 35px>
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Determine Determine   from the given matrix with orthogonal columns without using row operations.  <div style=padding-top: 35px> from the given matrix with orthogonal columns without using row operations.
Determine   from the given matrix with orthogonal columns without using row operations.  <div style=padding-top: 35px>
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Find the QR decomposition for the matrix Find the QR decomposition for the matrix   .<div style=padding-top: 35px> .
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Find the QR decomposition for the matrix Find the QR decomposition for the matrix   .<div style=padding-top: 35px> .
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If A is any matrix, then If A is any matrix, then   is diagonalizable.<div style=padding-top: 35px> is diagonalizable.
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If A is an If A is an   diagonalizable matrix, then there exists a diagonal matrix D and an orthogonal matrix P such that   .<div style=padding-top: 35px> diagonalizable matrix, then there exists a diagonal matrix D and an orthogonal matrix P such that If A is an   diagonalizable matrix, then there exists a diagonal matrix D and an orthogonal matrix P such that   .<div style=padding-top: 35px> .
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If Q is an orthogonal matrix, then If Q is an orthogonal matrix, then   .<div style=padding-top: 35px> .
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If A is symmetric, and If A is symmetric, and   and   with   , then   is orthogonal to   .<div style=padding-top: 35px> and If A is symmetric, and   and   with   , then   is orthogonal to   .<div style=padding-top: 35px> with If A is symmetric, and   and   with   , then   is orthogonal to   .<div style=padding-top: 35px> , then If A is symmetric, and   and   with   , then   is orthogonal to   .<div style=padding-top: 35px> is orthogonal to If A is symmetric, and   and   with   , then   is orthogonal to   .<div style=padding-top: 35px> .
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If If   is a QR factorization of a matrix A, then   .<div style=padding-top: 35px> is a QR factorization of a matrix A, then If   is a QR factorization of a matrix A, then   .<div style=padding-top: 35px> .
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Find the singular values for the matrix Find the singular values for the matrix   .<div style=padding-top: 35px> .
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Find the singular values for the matrix Find the singular values for the matrix   .<div style=padding-top: 35px> .
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Find a singular value decomposition for the matrix Find a singular value decomposition for the matrix   .<div style=padding-top: 35px> .
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Find a singular value decomposition for the matrix Find a singular value decomposition for the matrix   .<div style=padding-top: 35px> .
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Find a singular value decomposition for the matrix Find a singular value decomposition for the matrix   .<div style=padding-top: 35px> .
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Find a singular value decomposition for the matrix Find a singular value decomposition for the matrix   .<div style=padding-top: 35px> .
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Express the given matrix Express the given matrix   as an outer product expansion   , where   and   are the singular values of   .  <div style=padding-top: 35px> as an outer product expansion Express the given matrix   as an outer product expansion   , where   and   are the singular values of   .  <div style=padding-top: 35px> , where Express the given matrix   as an outer product expansion   , where   and   are the singular values of   .  <div style=padding-top: 35px> and Express the given matrix   as an outer product expansion   , where   and   are the singular values of   .  <div style=padding-top: 35px> are the singular values of Express the given matrix   as an outer product expansion   , where   and   are the singular values of   .  <div style=padding-top: 35px> .
Express the given matrix   as an outer product expansion   , where   and   are the singular values of   .  <div style=padding-top: 35px>
Question
Express the given matrix Express the given matrix   as an outer product expansion   , where     and   are the singular values of   .  <div style=padding-top: 35px> as an outer product expansion Express the given matrix   as an outer product expansion   , where     and   are the singular values of   .  <div style=padding-top: 35px> , where Express the given matrix   as an outer product expansion   , where     and   are the singular values of   .  <div style=padding-top: 35px> Express the given matrix   as an outer product expansion   , where     and   are the singular values of   .  <div style=padding-top: 35px> and Express the given matrix   as an outer product expansion   , where     and   are the singular values of   .  <div style=padding-top: 35px> are the singular values of Express the given matrix   as an outer product expansion   , where     and   are the singular values of   .  <div style=padding-top: 35px> .
Express the given matrix   as an outer product expansion   , where     and   are the singular values of   .  <div style=padding-top: 35px>
Question
Determine the numerical rank of a Determine the numerical rank of a   matrix with singular values   ,   ,   , and   , if   .<div style=padding-top: 35px> matrix with singular values Determine the numerical rank of a   matrix with singular values   ,   ,   , and   , if   .<div style=padding-top: 35px> , Determine the numerical rank of a   matrix with singular values   ,   ,   , and   , if   .<div style=padding-top: 35px> , Determine the numerical rank of a   matrix with singular values   ,   ,   , and   , if   .<div style=padding-top: 35px> , and Determine the numerical rank of a   matrix with singular values   ,   ,   , and   , if   .<div style=padding-top: 35px> , if Determine the numerical rank of a   matrix with singular values   ,   ,   , and   , if   .<div style=padding-top: 35px> .
Question
Determine the numerical rank of a Determine the numerical rank of a   matrix with singular values   ,   ,   ,   , and   , if   .<div style=padding-top: 35px> matrix with singular values Determine the numerical rank of a   matrix with singular values   ,   ,   ,   , and   , if   .<div style=padding-top: 35px> , Determine the numerical rank of a   matrix with singular values   ,   ,   ,   , and   , if   .<div style=padding-top: 35px> , Determine the numerical rank of a   matrix with singular values   ,   ,   ,   , and   , if   .<div style=padding-top: 35px> , Determine the numerical rank of a   matrix with singular values   ,   ,   ,   , and   , if   .<div style=padding-top: 35px> , and Determine the numerical rank of a   matrix with singular values   ,   ,   ,   , and   , if   .<div style=padding-top: 35px> , if Determine the numerical rank of a   matrix with singular values   ,   ,   ,   , and   , if   .<div style=padding-top: 35px> .
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Every matrix A has a singular value decomposition.
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The singular value decomposition of a matrix A is unique.
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If D is a diagonal matrix with diagonal entries If D is a diagonal matrix with diagonal entries   , then the singular values of D are given by   .<div style=padding-top: 35px> , then the singular values of D are given by If D is a diagonal matrix with diagonal entries   , then the singular values of D are given by   .<div style=padding-top: 35px> .
Question
If If   is a singular value decomposition for a matrix   , then   is an orthogonal diagonalizing matrix for   .<div style=padding-top: 35px> is a singular value decomposition for a matrix If   is a singular value decomposition for a matrix   , then   is an orthogonal diagonalizing matrix for   .<div style=padding-top: 35px> , then If   is a singular value decomposition for a matrix   , then   is an orthogonal diagonalizing matrix for   .<div style=padding-top: 35px> is an orthogonal diagonalizing matrix for If   is a singular value decomposition for a matrix   , then   is an orthogonal diagonalizing matrix for   .<div style=padding-top: 35px> .
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If If   is an invertible (square) matrix with singular value decomposition   , then a singular value decomposition for   is given by   .<div style=padding-top: 35px> is an invertible (square) matrix with singular value decomposition If   is an invertible (square) matrix with singular value decomposition   , then a singular value decomposition for   is given by   .<div style=padding-top: 35px> , then a singular value decomposition for If   is an invertible (square) matrix with singular value decomposition   , then a singular value decomposition for   is given by   .<div style=padding-top: 35px> is given by If   is an invertible (square) matrix with singular value decomposition   , then a singular value decomposition for   is given by   .<div style=padding-top: 35px> .
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Find the vector in the subspace S that is closest to y.
Find the vector in the subspace S that is closest to y.  <div style=padding-top: 35px>
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Find the vector in the subspace S that is closest to y.
Find the vector in the subspace S that is closest to y.  <div style=padding-top: 35px>
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Find the normal equations for the given system.
Find the normal equations for the given system.  <div style=padding-top: 35px>
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Find the normal equations for the given system.
Find the normal equations for the given system.  <div style=padding-top: 35px>
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Find the least squares solution for the given system.
Find the least squares solution for the given system.  <div style=padding-top: 35px>
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Find the least squares solution for the given system.
Find the least squares solution for the given system.  <div style=padding-top: 35px>
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Find the least squares solution for the given system.
Find the least squares solution for the given system.  <div style=padding-top: 35px>
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Find all least squares solutions for the given system.
Find all least squares solutions for the given system.  <div style=padding-top: 35px>
Question
Find an equation for the plane in Find an equation for the plane in   that best fits the given data.   ,   ,   ,  <div style=padding-top: 35px> that best fits the given data.
Find an equation for the plane in   that best fits the given data.   ,   ,   ,  <div style=padding-top: 35px> , Find an equation for the plane in   that best fits the given data.   ,   ,   ,  <div style=padding-top: 35px> , Find an equation for the plane in   that best fits the given data.   ,   ,   ,  <div style=padding-top: 35px> ,
Find an equation for the plane in   that best fits the given data.   ,   ,   ,  <div style=padding-top: 35px>
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Find an equation for the line in Find an equation for the line in   that best fits the given data.   ,   ,  <div style=padding-top: 35px> that best fits the given data.
Find an equation for the line in   that best fits the given data.   ,   ,  <div style=padding-top: 35px> , Find an equation for the line in   that best fits the given data.   ,   ,  <div style=padding-top: 35px> ,
Find an equation for the line in   that best fits the given data.   ,   ,  <div style=padding-top: 35px>
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Every system of equations has at least one least squares solution.
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If a matrix A has linearly independent columns, then for every vector y there exists a unique least squares solution of If a matrix A has linearly independent columns, then for every vector y there exists a unique least squares solution of   .<div style=padding-top: 35px> .
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If a system of equations has more variables than equations, then the system has infinitely many least squares solutions.
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If a system of equations has more equations than variables, then the system has a unique least squares solution.
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If If   is a matrix and   is in   , then   is a least squares solution to   .<div style=padding-top: 35px> is a matrix and If   is a matrix and   is in   , then   is a least squares solution to   .<div style=padding-top: 35px> is in If   is a matrix and   is in   , then   is a least squares solution to   .<div style=padding-top: 35px> , then If   is a matrix and   is in   , then   is a least squares solution to   .<div style=padding-top: 35px> is a least squares solution to If   is a matrix and   is in   , then   is a least squares solution to   .<div style=padding-top: 35px> .
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Deck 8: Orthogonality
1
Find all values of a so that u and v are orthogonal.
Find all values of a so that u and v are orthogonal.
2
Find all values of a so that u and v are orthogonal.
Find all values of a so that u and v are orthogonal.
3
Determine if the vectors form an orthogonal set.
Determine if the vectors form an orthogonal set.
The vectors form an orthogonal set.
4
Determine if the vectors form an orthogonal set.
Determine if the vectors form an orthogonal set.
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5
Find all values of a (if any) so that the given vectors form an orthogonal set.
Find all values of a (if any) so that the given vectors form an orthogonal set.
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6
Suppose Suppose   and   are orthogonal with   and   . Determine   . and Suppose   and   are orthogonal with   and   . Determine   . are orthogonal with Suppose   and   are orthogonal with   and   . Determine   . and Suppose   and   are orthogonal with   and   . Determine   . . Determine Suppose   and   are orthogonal with   and   . Determine   . .
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7
Determine all values of a so that the vector u is orthogonal to the subspace S.
Determine all values of a so that the vector u is orthogonal to the subspace S.
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8
Find a basis for Find a basis for   for the subspace S.  for the subspace S.
Find a basis for   for the subspace S.
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9
Find a basis for Find a basis for   for the subspace S.  for the subspace S.
Find a basis for   for the subspace S.
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10
Suppose S is a subspace of Suppose S is a subspace of   , and   . Determine   . , and Suppose S is a subspace of   , and   . Determine   . . Determine Suppose S is a subspace of   , and   . Determine   . .
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11
If If   is an orthogonal basis for a subspace S of   , and   then   is a diagonal   matrix. is an orthogonal basis for a subspace S of If   is an orthogonal basis for a subspace S of   , and   then   is a diagonal   matrix. , and If   is an orthogonal basis for a subspace S of   , and   then   is a diagonal   matrix. then If   is an orthogonal basis for a subspace S of   , and   then   is a diagonal   matrix. is a diagonal If   is an orthogonal basis for a subspace S of   , and   then   is a diagonal   matrix. matrix.
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12
If If   is a linearly independent set of vectors, then   is orthogonal. is a linearly independent set of vectors, then If   is a linearly independent set of vectors, then   is orthogonal. is orthogonal.
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13
If If   is an orthogonal set of vectors, and   , then   . is an orthogonal set of vectors, and If   is an orthogonal set of vectors, and   , then   . , then
If   is an orthogonal set of vectors, and   , then   . .
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14
If A is any matrix, then If A is any matrix, then   . .
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15
If S is a subspace of If S is a subspace of   , then   . , then If S is a subspace of   , then   . .
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16
Determine Determine   , where   . , where Determine   , where   . .
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17
Determine Determine   , where   . , where Determine   , where   . .
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18
Determine Determine   , where   ,   . , where Determine   , where   ,   . , Determine   , where   ,   . .
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19
Find an orthogonal basis for the subspace Find an orthogonal basis for the subspace   . .
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20
Find an orthogonal basis for the subspace Find an orthogonal basis for the subspace   . .
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21
Find an orthogonal basis for the subspace Find an orthogonal basis for the subspace   . .
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22
Find Find   , where   . , where Find   , where   . .
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23
Apply the Gram-Schmidt process to the given basis for Apply the Gram-Schmidt process to the given basis for   to produce an orthogonal basis for   . Then normalize the vectors to produce an orthonormal basis for   .  to produce an orthogonal basis for Apply the Gram-Schmidt process to the given basis for   to produce an orthogonal basis for   . Then normalize the vectors to produce an orthonormal basis for   .  . Then normalize the vectors to produce an orthonormal basis for Apply the Gram-Schmidt process to the given basis for   to produce an orthogonal basis for   . Then normalize the vectors to produce an orthonormal basis for   .  .
Apply the Gram-Schmidt process to the given basis for   to produce an orthogonal basis for   . Then normalize the vectors to produce an orthonormal basis for   .
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24
Find an orthonormal basis for the subspace Find an orthonormal basis for the subspace   . .
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25
Find an orthonormal basis for the subspace Find an orthonormal basis for the subspace   , and use it to to find   , where   . , and use it to to find Find an orthonormal basis for the subspace   , and use it to to find   , where   . , where Find an orthonormal basis for the subspace   , and use it to to find   , where   . .
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26
If S is a nonzero subspace of If S is a nonzero subspace of   , then for every vector u in   ,   belongs to S. , then for every vector u in If S is a nonzero subspace of   , then for every vector u in   ,   belongs to S. , If S is a nonzero subspace of   , then for every vector u in   ,   belongs to S. belongs to S.
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27
If If   is a nonzero subspace of   , and u belongs to   , then   . is a nonzero subspace of If   is a nonzero subspace of   , and u belongs to   , then   . , and u belongs to If   is a nonzero subspace of   , and u belongs to   , then   . , then If   is a nonzero subspace of   , and u belongs to   , then   . .
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28
If If   is a nonzero subspace of   , and u belongs to   , then   for every vector   . is a nonzero subspace of If   is a nonzero subspace of   , and u belongs to   , then   for every vector   . , and u belongs to If   is a nonzero subspace of   , and u belongs to   , then   for every vector   . , then If   is a nonzero subspace of   , and u belongs to   , then   for every vector   . for every vector If   is a nonzero subspace of   , and u belongs to   , then   for every vector   . .
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29
If If   and   are nonzero subspaces of   , then   for every vector u in   . and If   and   are nonzero subspaces of   , then   for every vector u in   . are nonzero subspaces of If   and   are nonzero subspaces of   , then   for every vector u in   . , then If   and   are nonzero subspaces of   , then   for every vector u in   . for every vector u in If   and   are nonzero subspaces of   , then   for every vector u in   . .
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30
If If   is an orthonormal set, then   is linearly independent. is an orthonormal set, then If   is an orthonormal set, then   is linearly independent. is linearly independent.
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31
Determine if the given matrix is symmetric.
Determine if the given matrix is symmetric.
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32
Determine if the given matrix is orthogonal.
Determine if the given matrix is orthogonal.
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33
The eigenvalues and corresponding eigenvectors for a symmetric matrix A are given. Find matrices D and P of an orthogonal diagonalization of A. The eigenvalues and corresponding eigenvectors for a symmetric matrix A are given. Find matrices D and P of an orthogonal diagonalization of A.
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34
The eigenvalues and corresponding eigenvectors for a symmetric matrix A are given. Find matrices D and P of an orthogonal diagonalization of A. The eigenvalues and corresponding eigenvectors for a symmetric matrix A are given. Find matrices D and P of an orthogonal diagonalization of A.
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35
The eigenvalues for the symmetric matrix A are given. Find matrices D and P of an orthogonal diagonalization of A. The eigenvalues for the symmetric matrix A are given. Find matrices D and P of an orthogonal diagonalization of A.
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36
The eigenvalues for the symmetric matrix A are given. Find matrices D and P of an orthogonal diagonalization of A. The eigenvalues for the symmetric matrix A are given. Find matrices D and P of an orthogonal diagonalization of A.
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37
Verify that the eigenvalues of Verify that the eigenvalues of   are nonnegative.  are nonnegative.
Verify that the eigenvalues of   are nonnegative.
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38
Determine Determine   from the given matrix with orthogonal columns without using row operations.  from the given matrix with orthogonal columns without using row operations.
Determine   from the given matrix with orthogonal columns without using row operations.
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39
Find the QR decomposition for the matrix Find the QR decomposition for the matrix   . .
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40
Find the QR decomposition for the matrix Find the QR decomposition for the matrix   . .
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41
If A is any matrix, then If A is any matrix, then   is diagonalizable. is diagonalizable.
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42
If A is an If A is an   diagonalizable matrix, then there exists a diagonal matrix D and an orthogonal matrix P such that   . diagonalizable matrix, then there exists a diagonal matrix D and an orthogonal matrix P such that If A is an   diagonalizable matrix, then there exists a diagonal matrix D and an orthogonal matrix P such that   . .
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43
If Q is an orthogonal matrix, then If Q is an orthogonal matrix, then   . .
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44
If A is symmetric, and If A is symmetric, and   and   with   , then   is orthogonal to   . and If A is symmetric, and   and   with   , then   is orthogonal to   . with If A is symmetric, and   and   with   , then   is orthogonal to   . , then If A is symmetric, and   and   with   , then   is orthogonal to   . is orthogonal to If A is symmetric, and   and   with   , then   is orthogonal to   . .
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45
If If   is a QR factorization of a matrix A, then   . is a QR factorization of a matrix A, then If   is a QR factorization of a matrix A, then   . .
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46
Find the singular values for the matrix Find the singular values for the matrix   . .
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47
Find the singular values for the matrix Find the singular values for the matrix   . .
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48
Find a singular value decomposition for the matrix Find a singular value decomposition for the matrix   . .
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49
Find a singular value decomposition for the matrix Find a singular value decomposition for the matrix   . .
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50
Find a singular value decomposition for the matrix Find a singular value decomposition for the matrix   . .
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51
Find a singular value decomposition for the matrix Find a singular value decomposition for the matrix   . .
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52
Express the given matrix Express the given matrix   as an outer product expansion   , where   and   are the singular values of   .  as an outer product expansion Express the given matrix   as an outer product expansion   , where   and   are the singular values of   .  , where Express the given matrix   as an outer product expansion   , where   and   are the singular values of   .  and Express the given matrix   as an outer product expansion   , where   and   are the singular values of   .  are the singular values of Express the given matrix   as an outer product expansion   , where   and   are the singular values of   .  .
Express the given matrix   as an outer product expansion   , where   and   are the singular values of   .
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53
Express the given matrix Express the given matrix   as an outer product expansion   , where     and   are the singular values of   .  as an outer product expansion Express the given matrix   as an outer product expansion   , where     and   are the singular values of   .  , where Express the given matrix   as an outer product expansion   , where     and   are the singular values of   .  Express the given matrix   as an outer product expansion   , where     and   are the singular values of   .  and Express the given matrix   as an outer product expansion   , where     and   are the singular values of   .  are the singular values of Express the given matrix   as an outer product expansion   , where     and   are the singular values of   .  .
Express the given matrix   as an outer product expansion   , where     and   are the singular values of   .
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54
Determine the numerical rank of a Determine the numerical rank of a   matrix with singular values   ,   ,   , and   , if   . matrix with singular values Determine the numerical rank of a   matrix with singular values   ,   ,   , and   , if   . , Determine the numerical rank of a   matrix with singular values   ,   ,   , and   , if   . , Determine the numerical rank of a   matrix with singular values   ,   ,   , and   , if   . , and Determine the numerical rank of a   matrix with singular values   ,   ,   , and   , if   . , if Determine the numerical rank of a   matrix with singular values   ,   ,   , and   , if   . .
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55
Determine the numerical rank of a Determine the numerical rank of a   matrix with singular values   ,   ,   ,   , and   , if   . matrix with singular values Determine the numerical rank of a   matrix with singular values   ,   ,   ,   , and   , if   . , Determine the numerical rank of a   matrix with singular values   ,   ,   ,   , and   , if   . , Determine the numerical rank of a   matrix with singular values   ,   ,   ,   , and   , if   . , Determine the numerical rank of a   matrix with singular values   ,   ,   ,   , and   , if   . , and Determine the numerical rank of a   matrix with singular values   ,   ,   ,   , and   , if   . , if Determine the numerical rank of a   matrix with singular values   ,   ,   ,   , and   , if   . .
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56
Every matrix A has a singular value decomposition.
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57
The singular value decomposition of a matrix A is unique.
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58
If D is a diagonal matrix with diagonal entries If D is a diagonal matrix with diagonal entries   , then the singular values of D are given by   . , then the singular values of D are given by If D is a diagonal matrix with diagonal entries   , then the singular values of D are given by   . .
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59
If If   is a singular value decomposition for a matrix   , then   is an orthogonal diagonalizing matrix for   . is a singular value decomposition for a matrix If   is a singular value decomposition for a matrix   , then   is an orthogonal diagonalizing matrix for   . , then If   is a singular value decomposition for a matrix   , then   is an orthogonal diagonalizing matrix for   . is an orthogonal diagonalizing matrix for If   is a singular value decomposition for a matrix   , then   is an orthogonal diagonalizing matrix for   . .
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60
If If   is an invertible (square) matrix with singular value decomposition   , then a singular value decomposition for   is given by   . is an invertible (square) matrix with singular value decomposition If   is an invertible (square) matrix with singular value decomposition   , then a singular value decomposition for   is given by   . , then a singular value decomposition for If   is an invertible (square) matrix with singular value decomposition   , then a singular value decomposition for   is given by   . is given by If   is an invertible (square) matrix with singular value decomposition   , then a singular value decomposition for   is given by   . .
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61
Find the vector in the subspace S that is closest to y.
Find the vector in the subspace S that is closest to y.
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62
Find the vector in the subspace S that is closest to y.
Find the vector in the subspace S that is closest to y.
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63
Find the normal equations for the given system.
Find the normal equations for the given system.
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64
Find the normal equations for the given system.
Find the normal equations for the given system.
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65
Find the least squares solution for the given system.
Find the least squares solution for the given system.
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66
Find the least squares solution for the given system.
Find the least squares solution for the given system.
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67
Find the least squares solution for the given system.
Find the least squares solution for the given system.
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68
Find all least squares solutions for the given system.
Find all least squares solutions for the given system.
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69
Find an equation for the plane in Find an equation for the plane in   that best fits the given data.   ,   ,   ,  that best fits the given data.
Find an equation for the plane in   that best fits the given data.   ,   ,   ,  , Find an equation for the plane in   that best fits the given data.   ,   ,   ,  , Find an equation for the plane in   that best fits the given data.   ,   ,   ,  ,
Find an equation for the plane in   that best fits the given data.   ,   ,   ,
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70
Find an equation for the line in Find an equation for the line in   that best fits the given data.   ,   ,  that best fits the given data.
Find an equation for the line in   that best fits the given data.   ,   ,  , Find an equation for the line in   that best fits the given data.   ,   ,  ,
Find an equation for the line in   that best fits the given data.   ,   ,
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71
Every system of equations has at least one least squares solution.
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72
If a matrix A has linearly independent columns, then for every vector y there exists a unique least squares solution of If a matrix A has linearly independent columns, then for every vector y there exists a unique least squares solution of   . .
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73
If a system of equations has more variables than equations, then the system has infinitely many least squares solutions.
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74
If a system of equations has more equations than variables, then the system has a unique least squares solution.
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75
If If   is a matrix and   is in   , then   is a least squares solution to   . is a matrix and If   is a matrix and   is in   , then   is a least squares solution to   . is in If   is a matrix and   is in   , then   is a least squares solution to   . , then If   is a matrix and   is in   , then   is a least squares solution to   . is a least squares solution to If   is a matrix and   is in   , then   is a least squares solution to   . .
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