M340L Exam 2 – Flashcards

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If A and B are 2 x 2 matrices with columns a1, a2, and b1, b2, respectively, then AB = [a1b1 a2b2].
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FALSE Matrix multiplication is "row by column".
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Each column of AB is a linear combination of the columns of B using weights from the corresponding column of A.
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FALSE Swap A and B then its true
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AB + AC = A(B + C)
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TRUE
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A^T + B^T = (A + B)^T
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TRUE
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I The transpose of a product of matrices equals the product of their transposes in the same order.
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FALSE The transpose of a product of matrices equals the product of their transposes in the reverse order.
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I If A and B are 3 x 3 and B = [b1 b2 b3], then AB = [Ab1 + Ab2 + Ab3].
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FALSE This is right but there should not be +'s in the solution. Remember the answer should also be 3 x 3.
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The second row of AB is the second row of A multiplied on the right by B.
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TRUE
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(AB)C = (AC)B
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FALSE Matrix multiplication is not commutative.
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(AB)^T = A^T B^T
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FALSE (AB)^T = B^T A^T
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The transpose of a sum of matrices equals the sum of their transposes.
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TRUE
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A product of invertible n x n matrices is invertible, and the inverse of the product of their matrices in the same order.
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FALSE. It is invertible, but the inverses in the product of the inverses in the reverse order.
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If A is invertible, then the inverse of A^-1 is A itself.
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TRUE
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If A = [a b; c d] and ad = bc, then A is not invertible.
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TRUE
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If A can be row reduced to the identity matrix, then A must be invertible.
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TRUE
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I If A is invertible, then elementary row operations then reduce A to to the identity also reduce A^-1 to the identity
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FALSE They also reduce the identity to A^-1
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An n x n determinant is defined by determinants of (n - 1) x (n - 1) submatrices.
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TRUE
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The (i , j)-cofactor of a matrix A is the matrix Aij obtained by deleting from A its ith row and jth column.
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FALSE The cofactor is the determinant of this Aij times -1^i+j
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The cofactor expansion of det A down a column is the negative of the cofactor expansion along a row
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FALSE We can expand down any row or column and get same determinant.
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The determinant of a triangular matrix is the sum of the entries of the main diagonal.
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FALSE It is the product of the diagonal entries.
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A row replacement operation does not affect the determinant of a matrix.
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TRUE
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The determinant of A is the product of the pivots in any echelon form U of A, multiplied by (-1)^r, where r is the number of row interchanges made during row reduction from A to U
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FALSE If we scale any rows when getting the echelon form, we change the determinant
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If the columns of A are linearly dependent, then det A = 0.
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TRUE
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det(A + B) = det A + det B
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FALSE This is true for product however.
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If two row interchanges are made in succession, then the new determinant equals the old determinant
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TRUE
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The determinant of A is the product of the diagonal entries in A
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FALSE unless A is triangular
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If det A is zero, then two rows or two columns are the same, or a row or a column is zero.
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FALSE The converse is true, however.
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det(A^T) = (-1)detA
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FALSE det(A^T) = detA when A is n x n.
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If f is a function in the vector space V of all real-valued functions on R and if f(t) = 0 for some t, then f is the zero vector in V
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FALSE we need f(t) = 0 for all t
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A vector is an arrow in three-dimensional space.
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FALSE This is an example of a vector, but there are certainly vectors not of this form.
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A subset H of a vector space V, is a subspace of V if the zero vector is in H
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FALSE We also need the set to be closed under addition and scalar multiplication.
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A subspace is also a vector space.
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TRUE
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Analogue signals are used in the major control systems for the space shuttle, mentioned in the introduction to the chapter
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FALSE digital signals are used
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A vector is any element of a vector space
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TRUE
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If u is a vector in a vector space V, then (-1)u is the same as the negative of u.
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TRUE
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A vector space is also a subspace.
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TRUE
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R^2 is a subspace of R^3
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FALSE The elements in R^2 aren't even in R^3
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A subset H of a vector space V is a subspace of V if the following conditions are satised: (i) the zero vector of V is in H, (ii)u, v and u + v are in H, and (iii) c is a scalar and cu is in H
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FALSE The second and third parts aren't stated correctly
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The null space of A is the solution set of the equation Ax = 0.
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TRUE
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The null space of an m x n matrix is in R^m
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FALSE It's R^n
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The column space of A is the range of the mapping x -> Ax.
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TRUE
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If the equation Ax = b is consistent, then Col A is R^m
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FALSE must be consistent for all b
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The kernel of a linear transformation is a vector space
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TRUE
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Col A is the set of a vectors that can be written as Ax for some x.
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TRUE
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The null space is a vector space
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TRUE
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The column space of an m x n matrix is in R^m
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TRUE
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Col A is the set of all solutions of Ax = b
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FALSE It is the set of all b that have solutions
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Nul A is the kernel of the mapping x -> Ax
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TRUE
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The range of a linear transformation is a vector space.
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TRUE
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The set of all solutions of a homogeneous linear differential equation is the kernel of a linear transformation.
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TRUE
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A single vector is itself linearly dependent
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FALSE unless it is in the zero vector
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If H = Span {b1,...,bn} then {b1,...,bn} is a basis for H
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FALSE They may not be linearly independent
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The columns of an invertible n x n matrix form a basis for R^n
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TRUE
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A basis is a spanning set that is as large as possible.
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FALSE it is too large, then it is no longer linearly independent
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In some cases, the linear dependence relations among the columns of a matrix can be aected by certain elementary row operations on the matrix
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FALSE they are not affected
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A linearly independent set in a subspace H is a basis for H
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FALSE it may not span
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If a finite set S of nonzero vectors spans a vector space V, the some subset is a basis for V
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TRUE
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A basis is a linearly independent set that is as large as possible.
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TRUE
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The standard method for producing a spanning set for Nul A, described in this section, sometimes fails to produce a basis
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FALSE it never fails!
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If B is an echelon form of a matrix A, then the pivot columns of B form a basis for Col A
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FALSE Must look at corresponding columns in A
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4.4 15 a
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4.4 15 b
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4.4 15 c
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4.4 16 a
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4.4 16 b
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4.4 16 c
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The number of pivot columns of a matrix equals the dimension of its column space
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TRUE
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A plane in R^3 is a two dimensional subspace of R^3
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FALSE unless the plane is through the origin
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The dimension of the vector space P4 is 4
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FALSE It's 5
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If dimV = n and S is a linearly independent set in V, then S is a basis for V
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FALSE S must have exactly n elements
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If a set {v1...vn} spans a finite dimensional vector space V and if T is a set of more than n vectors in V, then T is linearly dependent
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TRUE
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R^2 is a two dimensional subspace of R^3
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FALSE Not a subset, as before
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The number of variables in the equation Ax = 0 equals the dimension of Nul A
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FALSE It's the number of free variables
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A vector space is infinite dimensional is it is spanned by an infinite set
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FALSE it must be impossible to span it by a finite set
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If dim V = n and if S spans V. then S is a basis for V
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FALSE S must have exactly n elements or be noted as linearly independent
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The only three dimensional subspace of R^3 is R^3 itself
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TRUE
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The row space of A is the same as the column space of A^T
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TRUE
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If B is an echelon form of A, and if B has three nonzero rows, then the first three rows of A form a basis of Row A
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FALSE The nonzero rows of B form a basis. The first three rows of A may be linear dependent.
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The dimensions of the row space and the column space of A are the same, even if A is not square
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TRUE
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The sum of the dimensions of the row space and the null space of A equals the number of rows in A
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FALSE Equals number of columns by rank theorem
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On a computer, row operations can change the apparent rank of a matrix.
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TRUE
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If B is any echelon form of A, the the pivot columns of B form a basis for the column space of A
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FALSE It's the corresponding columns in A
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Row operations preserve the linear dependence relations among the rows of A
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FALSE for example, row interchanges mess things up
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The dimension of null space of A is the number of columns of A that are not pivot columns
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TRUE
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The row space of A^T is the same as the column space of A
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TRUE
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If A and B are row equivalent, then their row spaces are the same
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TRUE
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