MATH 218 Final, Fall 2006

American University of Beirut · Elementary Linear Algebra with Applications · 11 pages

All MATH 218 files
MATH 218 Final, Fall 2006, page 1

Stuck on a question? A tutor can walk you through it.

MATH 218 Final, Fall 2006, page 2 MATH 218 Final, Fall 2006, page 3 MATH 218 Final, Fall 2006, page 4 MATH 218 Final, Fall 2006, page 5 MATH 218 Final, Fall 2006, page 6 MATH 218 Final, Fall 2006, page 7 MATH 218 Final, Fall 2006, page 8 MATH 218 Final, Fall 2006, page 9 MATH 218 Final, Fall 2006, page 10

Showing the first 10 of 11 pages. Download the PDF to see all of it.

More MATH 218 files

Show the text of this final exam
AMERICAN UNIVERSITY OF BEIRUT Mathematics Department Math 218 - Final Exam Fall 2006-2007 Name:........................................ ID:............................................. Section: 4 (@ 12:30) 5 (@ 9:30) Time: 120 min Directions: • Read each question carefully before you answer. • If you are asked to answer by TRUE or FALSE, make sure that you do not give an abrupt answer. I- Give a precise definition of the following: (a) (4 points) A vector space: (b) (3 points) A basis for a vector space: 1 (c) (3 points) The rank of a matrix: (d) (3 points) A linear transformation between two vector spaces: (e) (3 points) The nullity of a linear transformation: II- Let A =   1 4 −3 0 2 10 0 4 3 13 −7 3   (a) (2.5 points)Find a basis for the row space of A. 2 (continue your answer here) (b) (2.5 points) Find a basis for the column space of A. 3 (c) (3 points) Use (b) to show that the system   1 4 −3 2 10 0 3 13 −7   x =   0 4 3   is consistent, without solving it. III- Let B =   1 1 1 0 2 2 0 0 3   (a) (4 points) Find the eigenvalues of B. (c) (8 points) Find bases for the eigenspaces of B. 4 (Continue your answer here) (b) (5 points) Is B diagonalizable? If yes, find a matrix P that diagonalizes B and determine P −1BP. IV- Consider the system Ax = b. (a) (i) (6 points) Find a least squares solution for the system if: A =   2 1 −2 1 0 −1 1 1 0 1 1 −1   and b =   6 3 9 6   5 (Continue your answer here) (ii) (4 points) Find the orthogonal projection of u = (6, 3, 9, 6) on the subspace of R4 spanned by the vectors v1 = (2, 1, 1, 1), v2 = (1, 0, 1, 1), and v3 = (−2, −1, 0, −1). (b) (3 points) If b is in the null space of AT. What is Proj W b ? Justify. 6 V- Let T be a function from the vector space of all n × n matrices Mnn to itself with standard addition and scalar multiplication. Let C be a fixed n × n invertible matrix. Define T by T(A) = CA for all A ∈ Mnn. (a) (4 points) Show that T is a linear transformation. (b) (5 points) Show that T is one-to-one. (c) (5 points) Deduce rank(T). 7 (Continue your answer here) (c) (3 points) Is T is an isomorphism? Explain. VI- Let T be a linear transformation from the vector space P2 to the vector space R2 with standard addition and scalar multiplication defined by: T(p(x)) = ( p(0) , p(−1) + p(1) ) (a) (5 points) Let B = {1, x2, x} and B′ = {e1, e2}. Find B′[T]B. 8 (b) (5 points) Define, then find ker(T). VII- (8 points) If T : V −→ W is a one-to-one linear transformation and {v1, v2, ..., vn} is a basis for V , then {T(v1), T(v2), ..., T(vn)} is linearly independent in W. 9 VIII- (5 points) Specify the appropriate vector space, operations and inner product , then, use Cauchy Schwarz inequality to show that for all positive numbers a1, a2, ..., an, (a1 + 2a2 + ... + nan) � 1 a1 + 2 a2 + ... + n an � ⩾ n2(n + 1)2 4 10 IX- (6 points) Write TRUE or FALSE. 1- If λ is an eigenvalue of an invertible matrix A, then 1 λ is an eigenvalue of A−1. 2- If v is an eigenvector of a square matrix A, then it is also an eigenvector of A5. 3- If det(A) = √ 3 then λ = 0 is an eigenvalue of A. 4- If T : R5 −→ M33 and rank(T) = 5 then T is not one-to-one. 5- The matrix ATA − 3I is orthogonally diagonalizable for any matrix A. 6- If {v1, v2, ..., vn} is an orthogonal set of nonzero vectors in an inner product space V such that dim(V ) = m , then m ⩽ n. GOOD LUCK If you have any comments or requests, please write them here: 11