W is an n x n matrix.
T F if the rows of W are linearly independent, then the detW is not equal to zero
T F if the detW is not equal to zero, then the rank of W is equal to n.
T F if Wx = V has a unique solution for every V in Rn, then the detW is not equal to zero.
T F if null(W) = {0}, then the detW is equal to zero.
T F if det(W - λi) = 0, then Wx = 0 has infinitely many solutions
T F if λ = 0 is an eigenvalue of W, then W is invertible


5. This problem is to help you relate many of the topics we have discussed this semester. Fill in the blanks Let A be an n × n matrix. A is nonsingular if and only if (a) The homogeneous linear system A0 has b) A is row equivalent to (c) The rank of A is (d) Theof A are linearly independent (e) Theof A span (f) The (g) N(A) = of R" Of A form a (i) The map V...
a.) if A is an m*n matrix, such that Ax=0 for every vector x in R^n, then A is the m * n Zero matrix b.) The row echelon form of an invertible 3 * 3 matrix is invertible c.) If A is an m*n matrix and the equation Ax=0 has only the trivial solution, then the columns of A are linearly independent. d.) If T is the linear transformation whose standard matrix is an m*n matrix A and the...
Write each statement as True or False (a) If an (nx n) matrix A is not invertible then the linear system Ax-O hns infinitely many b) If the number of equations in a linear system exceeds the number of unknowns then the system 10p solutions must be inconsistent ) If each equation in a consistent system is multiplied through by a constant c then all solutions to the new system can be obtained by multiplying the solutions to the original...
linear algebra question
2. (5' each) Give short answers: (a) True or false: If Ai-Adi for some real number λ, then u is an eigenvector of matrix A. If a square matrix is diagonalizable, then it has n distinct real eigenvalues. Two vectors of the same dimension are linearly independent if and only if one is not a multiple of the other. If the span of a set of vectors is R", then that set is a basis of R...
P4. Prove: If V = {V1, V2, ...,V) is a linearly indepen- dent set of vectors in R", and if W = {Wx+1, ...,wn} is a basis for the null space of the matrix A that has the vectors V1, V2, ..., Vk as its successive rows, then VUW = {V1, V2, ..., Vk, Wk+1,...,w.} is a basis for R". [Hint: Since V UW contains n vectors, it suffices to show that VUW is linearly independent. As a first step,...
Problem 3. Let V and W be vector spaces of dimensions n and m, respectively, and let T : V -> W be a linear transformation. (a) Prove that for every pair of ordered bases B = exists a unique m x n matrix A such that [T(E)]c = A[r3 for all e V. The matrix A is called the (B,C)-matrix of T, written A = c[T]b. (b) For each n E N, let Pm be the vector space of...
Explain why the columns of an nxn matrix A are linearly independent when A is invertible Choose the correct answer below. O A. IFA is invertible, then for all x there is a b such that Ax=b. Since x = 0 is a solution of Ax0, the columns of A must be linearly independent OB. IA is invertible, then A has an inverse matrix A Since AA A AA must have linearly independent columns O C. If A is invertible,...
Problem 16 (10 pts) For an n x n matrix A, pa(t) = t.q(t) for some polynomial q(t) precisely when Det(A) = 0. Problem 17 (10 pts) If W CR” is a subspace and v eR”, then pw(v) is the least-squares approximation to v by a vector in W except when pw(v) = 0. Problem 18 (10 pts) If A is a real n xn matrix, then the pairing defined by <v, w >:=yT * AT * A* w is...
Problem 3. Let V and W be vector spaces of dimensions n and m, respectively, and let T : V -> V be a linear transformation (a) Prove that for every pair of ordered bases B = (Ti,...,T,) of V and C = (Wi, ..., Wm) of W, then exists a unique (B, C)-matrix of T, written A = c[T]g. (b) For each n e N, let Pn be the vector space of polynomials of degree at mostn in the...
Review 4: question 1 Let A be an n x n matrix. Which of the below is not true? A. A scalar 2 is an eigenvalue of A if and only if (A - 11) is not invertible. B. A non-zero vector x is an eigenvector corresponding to an eigenvalue if and only if x is a solution of the matrix equation (A-11)x= 0. C. To find all eigenvalues of A, we solve the characteristic equation det(A-2) = 0. D)....