Linear Algebra 1 Exam 2 Solutions 7/14/3

Similar documents
Exam 2 Solutions. (a) Is W closed under addition? Why or why not? W is not closed under addition. For example,

1. What is the determinant of the following matrix? a 1 a 2 4a 3 2a 2 b 1 b 2 4b 3 2b c 1. = 4, then det

Math 369 Exam #2 Practice Problem Solutions

Chapter 3. Vector spaces

MATH 304 Linear Algebra Lecture 10: Linear independence. Wronskian.

MATH 304 Linear Algebra Lecture 20: Review for Test 1.

Chapter 2 Notes, Linear Algebra 5e Lay

SECTION 3.3. PROBLEM 22. The null space of a matrix A is: N(A) = {X : AX = 0}. Here are the calculations of AX for X = a,b,c,d, and e. =

(b) The nonzero rows of R form a basis of the row space. Thus, a basis is [ ], [ ], [ ]

CSL361 Problem set 4: Basic linear algebra

Chapter 1. Vectors, Matrices, and Linear Spaces

Abstract Vector Spaces

MATH 323 Linear Algebra Lecture 12: Basis of a vector space (continued). Rank and nullity of a matrix.

Math 314H EXAM I. 1. (28 points) The row reduced echelon form of the augmented matrix for the system. is the matrix

Math 240, 4.3 Linear Independence; Bases A. DeCelles. 1. definitions of linear independence, linear dependence, dependence relation, basis

Study Guide for Linear Algebra Exam 2

Math 54 HW 4 solutions

b for the linear system x 1 + x 2 + a 2 x 3 = a x 1 + x 3 = 3 x 1 + x 2 + 9x 3 = 3 ] 1 1 a 2 a

1. Determine by inspection which of the following sets of vectors is linearly independent. 3 3.

Mathematics I. Exercises with solutions. 1 Linear Algebra. Vectors and Matrices Let , C = , B = A = Determine the following matrices:

Linear Algebra Practice Problems

MATH 1120 (LINEAR ALGEBRA 1), FINAL EXAM FALL 2011 SOLUTIONS TO PRACTICE VERSION

MA 242 LINEAR ALGEBRA C1, Solutions to First Midterm Exam

2018 Fall 2210Q Section 013 Midterm Exam II Solution

Final Examination 201-NYC-05 December and b =

Math 353, Practice Midterm 1

Review 1 Math 321: Linear Algebra Spring 2010

2.3. VECTOR SPACES 25

Linear Algebra 1 Exam 1 Solutions 6/12/3

Math 1553, Introduction to Linear Algebra

MODEL ANSWERS TO THE FIRST QUIZ. 1. (18pts) (i) Give the definition of a m n matrix. A m n matrix with entries in a field F is a function

ICS 6N Computational Linear Algebra Vector Space

MATH 20F: LINEAR ALGEBRA LECTURE B00 (T. KEMP)

BASIC NOTIONS. x + y = 1 3, 3x 5y + z = A + 3B,C + 2D, DC are not defined. A + C =

Math 4377/6308 Advanced Linear Algebra

EXERCISE SET 5.1. = (kx + kx + k, ky + ky + k ) = (kx + kx + 1, ky + ky + 1) = ((k + )x + 1, (k + )y + 1)

2. Every linear system with the same number of equations as unknowns has a unique solution.

MATH 2360 REVIEW PROBLEMS

Chapter 1 Vector Spaces

MAT 242 CHAPTER 4: SUBSPACES OF R n

Vector Spaces 4.4 Spanning and Independence

MATH 213 Linear Algebra and ODEs Spring 2015 Study Sheet for Midterm Exam. Topics

Math Exam 2, October 14, 2008

Final Examination 201-NYC-05 - Linear Algebra I December 8 th, and b = 4. Find the value(s) of a for which the equation Ax = b

MATH Topics in Applied Mathematics Lecture 12: Evaluation of determinants. Cross product.

MATH10212 Linear Algebra B Homework Week 4

Review Notes for Midterm #2

2018 Fall 2210Q Section 013 Midterm Exam I Solution

Math 224, Fall 2007 Exam 3 Thursday, December 6, 2007

Solutions to Final Exam

Permutations and Polynomials Sarah Kitchen February 7, 2006

MATH 3321 Sample Questions for Exam 3. 3y y, C = Perform the indicated operations, if possible: (a) AC (b) AB (c) B + AC (d) CBA

Math 3108: Linear Algebra

Chapter 3. Directions: For questions 1-11 mark each statement True or False. Justify each answer.

YORK UNIVERSITY. Faculty of Science Department of Mathematics and Statistics MATH M Test #1. July 11, 2013 Solutions

MAT Linear Algebra Collection of sample exams

MTH501- Linear Algebra MCQS MIDTERM EXAMINATION ~ LIBRIANSMINE ~

MATH 152 Exam 1-Solutions 135 pts. Write your answers on separate paper. You do not need to copy the questions. Show your work!!!

EXAM. Exam #2. Math 2360 Summer II, 2000 Morning Class. Nov. 15, 2000 ANSWERS

Linear Algebra Final Exam Study Guide Solutions Fall 2012

Homework #6 Solutions

Linear Algebra- Final Exam Review

Math 54. Selected Solutions for Week 5

Instructions Please answer the five problems on your own paper. These are essay questions: you should write in complete sentences.

MATH 2331 Linear Algebra. Section 1.1 Systems of Linear Equations. Finding the solution to a set of two equations in two variables: Example 1: Solve:

An overview of key ideas

SUMMARY OF MATH 1600

Abstract Vector Spaces and Concrete Examples

Linear Equations in Linear Algebra

NAME MATH 304 Examination 2 Page 1

Lecture 3: Linear Algebra Review, Part II

Math 250B Midterm II Information Spring 2019 SOLUTIONS TO PRACTICE PROBLEMS

Extra Problems for Math 2050 Linear Algebra I

There are six more problems on the next two pages

Carleton College, winter 2013 Math 232, Solutions to review problems and practice midterm 2 Prof. Jones 15. T 17. F 38. T 21. F 26. T 22. T 27.

MATH 300, Second Exam REVIEW SOLUTIONS. NOTE: You may use a calculator for this exam- You only need something that will perform basic arithmetic.

No books, notes, any calculator, or electronic devices are allowed on this exam. Show all of your steps in each answer to receive a full credit.

Math 3191 Applied Linear Algebra

(i) [7 points] Compute the determinant of the following matrix using cofactor expansion.

MATH 2210Q MIDTERM EXAM I PRACTICE PROBLEMS

Math 2940: Prelim 1 Practice Solutions

LINEAR SYSTEMS AND MATRICES

3.2 Subspace. Definition: If S is a non-empty subset of a vector space V, and S satisfies the following conditions: (i).

5.) For each of the given sets of vectors, determine whether or not the set spans R 3. Give reasons for your answers.

is Use at most six elementary row operations. (Partial

Hints and Selected Answers to Homework Sets

The converse is clear, since

MATH 315 Linear Algebra Homework #1 Assigned: August 20, 2018

Chapter 5. Linear Algebra. A linear (algebraic) equation in. unknowns, x 1, x 2,..., x n, is. an equation of the form

Linear Algebra Exam 1 Spring 2007

MATH Topics in Applied Mathematics Lecture 2-6: Isomorphism. Linear independence (revisited).

Review Solutions for Exam 1

Practice Final Exam Solutions

Linear Algebra. Session 8

Row Space, Column Space, and Nullspace

Vector Spaces ปร ภ ม เวกเตอร

IMPORTANT DEFINITIONS AND THEOREMS REFERENCE SHEET

Solutions to Midterm 2 Practice Problems Written by Victoria Kala Last updated 11/10/2015

Online Exercises for Linear Algebra XM511

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS. + + x 1 x 2. x n 8 (4) 3 4 2

Transcription:

Linear Algebra 1 Exam Solutions 7/14/3 Question 1 The line L has the symmetric equation: x 1 = y + 3 The line M has the parametric equation: = z 4. [x, y, z] = [ 4, 10, 5] + s[10, 7, ]. The line N is perpendicular to both the lines L and M and passes through the point [, 1, 3]. Find the parametric and symmetric equations of the line N. A direction vector for N is the cross product of the direction vectors of L and M: n = [1,, ] [10, 7, ] = det i j k 1 10 7 = i( 4 14) j( + 0) + k( 7 0) = 18i 18j 7k. Dividing by 9, we may take the direction vector to be [,, 3]. Then the parametric and symmetric equations of the line N are: [x, y, z] = [, 1, 3] + t[,, 3] = [ + t, 1 + t, 3 + 3t], x = y + 1 = z + 3 3. Show that the lines L and N meet and find the intersection point P. We put the parametric equation of N into the equation of L and solve for t: + t 1 + t + 3 3 + 3t 4 = =. 1 The first equation gives: t = t + 1, so t = 1 and when t = 1, these equations hold. So L and N meet at the point with t = 1, so at the point P = [4, 1, 0].

Show that the lines M and N meet and find the intersection point Q. We put the parametric equation of M into the symmetric equation of N and solve for s: 4 + 10s 10 7s + 1 = = 5 s + 3. 3 The first equation gives: 10s 6 = 11 7s, so s = 1 and when s = 1, these equations hold. So L and N meet at the point with s = 1, so at the point Q = [6, 3, 3]. Calculate the distance P Q. The distance P Q is : Question P Q = (6 4) + (3 1) + (3 0) = 4 + 4 + 9 = 17. Let A = (, 3, 5), B = (1, 1, 6), C = (,, 4). Find the equation of the plane ABC. Two vectors in the plane are : AB = B A = (1, 1, 6) (, 3, 5) = ( 1, 4, 1), AC = C A = (,, 4) (, 3, 5) = (0, 1, 1). So a normal, n, to the plane is: n = AB AC = det So the equation of the plane is: i j k 1 4 1 0 1 1 = i(4 + 1) j(1 0) + k(1 0) = 5i j + k [5, 1, 1].[x, y, z] = [5, 1, 1].[, 3, 5] = 10 3 + 5 = 1, 5x y + z = 1. We may check that A, B and C all lie on this plane, as required.

Find the area of the triangle ABC. The triangle has area: 1 n = 1 3 3 5 + 1 + 1 =. How far is the point D = (, 4, 7) from the plane ABC? We need the component of AD in the direction of n: AD.ˆn = 1 1 ([, 4, 7] [, 3, 5]).[5, 1, 1] = (1 1) = 3. n 7 So the point D is at a distance from the plane of 3 units of distance. Find the parametric equation of the line L through D perpendicular to the plane ABC. The vector n is a direction vector for the line L, so the line L has the parametric equation: [x, y, z] = [, 4, 7] + t[5, 1, 1] = [ + 5t, 4 t, 7 + t]. Find the point where the line L meets the plane ABC. We insert the formulas for x, y and z for the line L into the equation of the plane and solve for t: 5( + 5t) ( 4 t) + 7 + t = 1, 1 + 7t = 1, t = 1 3. So the required point is [ 5 3, 4 + 1 3, 7 1 3 ] = 1 3 [1, 11, 0]. It is easy to check that this point does indeed lie on the plane, as required.

Question 3 Which of the following subsets of vector spaces are subspaces. Explain your answers: The span S of the vectors [, 3, 1] and [4, 6, 1] in R 3. The span of any subset of a vector space is a subspace and this is no exception! The intersection of S with the plane in R 3 with equation: x + 4y + 9z = 5. A subspace must contain the zero vector, but x = y = z = t = 0 does not satisfy the given equation. So the given intersection does not contain the zero vector, so is not a subspace. The set T of all polynomials p(x) in P (the vector space of all polynomials in the variable x) such that only even powers of x occur in p, i.e. p(x) = p( x). If p(x) is a sum of multiples of even powers of x, then so is sp(x) for any scalar s, since multiplying by a scalar cannot change an even power to an odd power. More formally, we have: (sp)(x) (sp)( x) = sp(x) sp( x) = s(p(x) p( x)) = 0. So the polynomial sp is even, if p is, for any scalar s. So the set T is closed under scalar multiplication. Next, if p(x) and q(x) are each sums of multiples of even powers of x, then so is (p + q)(x) = p(x) + q(x) since addition of polynomials cannot change an even power to an odd power. More formally, we have: (p + q)(x) (p + q)( x) = p(x) + q(x) (p( x) + q( x)) = (p(x) p( x)) + (q(x) q( x)) = 0 + 0 = 0.

So the polynomial p + q is even, if p and q are. So the set T is closed under addition. So the set T is a subspace of P. The set U of all polynomials p(x) in P 3 (the vector space of all polynomials in the variable x of degree no more than three), such that p(0) = p(1). If we write p(x) = ax 3 +bx +cx+d, then p(0) = d and p(1) = a+b+c+d. So the condition p(0) = p(1) gives the equation a + b + c = 0, so a = b c. Then p(x) = ( b c)x 3 + bx + cx + d = d(1) + b(x x 3 ) + c(x x 3 ), where b, c and d are arbitrary. So the space U is the span of the polynomials 1, x x 3 and x x 3, so is a subspace. The intersection T U. The sets T and U may each be regarded as subspaces of P and the intersection of subspaces of a vector space is itself a subspace, so T U is a subspace of P and of P 3.

Question 4 Calculate the determinant of the following matrix B(t): B(t) = t 1 5 t det(b(t)) = ( t)(5 t) ( 1)() = t 7t+10+ = t 7t+1 = (t 3)(t 4). Find the values of t for which the matrix B(t) has no inverse. The matrix has no inverse iff it has zero determinant, iff t = 3 or t = 4. For which values of t does the homogeneous system with coefficient matrix B(t) have a non-trivial solution? The homogeneous system with coefficient matrix B(t) has a non-trivial solution iff B(t) has rank less than two, iff B(t) has no inverse, iff det(b(t)) = 0, iff t = 3 or t = 4. Let these values be t = t 1 and t = t. We put t 1 = 3 and t = 4. Find a non-trivial solution X 1 of the homogeneous system with coefficient matrix B(t 1 ). We have: B(t 1 ) = B(3) = 1 1 1 0 0. The reduced system is x y = 0. So we may pick y = s and then x = s. So the general solution is [x, y] = s[, 1], with s arbitrary. Taking s = 1, we may take X 1 = [, 1].

Find a non-trivial solution X of the homogeneous system with coefficient matrix B(t ). We have: B(t ) = B(4) = 1 1 1 1 0 0. The reduced system is x y = 0. So we may pick y = t and then x = t. So the general solution is [x, y] = t[1, 1], with t arbitrary. Taking t = 1, we may take X = [1, 1]. Show that X 1 and X are linearly independent. If px 1 + qx = 0, then we have: p[, 1] + q[1, 1] = [p + q, p + q] = [0, 0]. So p + q = 0 and p + q = 0. Subtracting these equations gives p = 0. Back substitution into the second equation gives q = 0. So p = q = 0 and the vectors X 1 and X are linearly independent. Show that X 1 and X span R. We see that e 1 = [1, 0] = X 1 X and e = [0, 1] = X 1 + X, so both e 1 and e lie in the span of X 1 and X. So all vectors in R lie in the span of X 1 and X, as required: Explicitly, we have for any [x, y] in R : [x, y] = xe 1 +ye = x(x 1 X )+y( X 1 +X ) = (x y)x 1 +(y x)x. Check: (x y)x 1 + (y x)x = (x y)[, 1] + (y x)[1, 1] = [x y, x y] + [y x, y x] = [x, y]

Question 5 Let A, B and C be the following polynomials in P : A = x 3x +, B = x 6x + 8, C = x ax + 4. Here a is a constant. Find the value of a such that A,B and C are linearly dependent. We want, for scalars p, q and r: 0 = pa + qb + rc = p(x 3x + ) + q(x 6x + 8) + r(x ax + 4) = x (p + q + r) + x( 3p 6q ar) + p + 8q + 4r. So we obtain the linear system: p + q + r = 0, 3p 6q ar = 0, p + 8q + 4r = 0. The first equation gives p = q r. Substituting in the third equation, we get 0 = q r + 8q + 4r = 6q + r. So r = 3q and then p = q r = q + 3q = q. Substituting in the second equation of our system, we get the remaining equation: 0 = 3(q) 6q a( 3q) = 1q + 3aq = 3q(a 4). If a 4, then q = 0 and then p = q = r = 0 and the polynomials are linearly independent. If a = 4, the last equation is satisfied and we have [p, q, r] = s[, 1, 3], with s arbitrary. In particular, we have A + B 3C = 0, when a = 4 and the polynomails are linearly dependent, as required. So the required value of a is 4. For that value of a, find a non-trivial linear relation between the polynomials A, B and C. As shown above such a relation is A + B 3C = 0.

Show that the polynomial D = x +7x 18 lies in the span of {A, B, C}. The span of {A, B, C} equals the span of {A, B}, since C is a combination of A and B. So it is sufficient to write D in terms of A and B. So we need: x + 7x 18 = p(x 3x + ) + q(x 6x + 8). Put x = 4 and B vanishes, so we get: 16 + 8 18 = 6 = p(16 1 + ) = 6p. Put x = 1 and A vanishes, so we get: 1 + 7 18 = 10 = q(1 6 + 8) = 3q. So (p, q) = ( 13, 10). 3 3 Check: 13 3 A 10 3 B = 1 3 (13x 39x + 6 10x + 60x 80) = 1 3 (3x + 1x 54) = x + 7x 18 = D. Do the polynomials A, B, C span P? Explain your answer. When a = 4 all the polynomials A, B and C have the factor x so any polynomial in their span also has that factor. But, for example, the polynomial x has no factor of x, so cannot lie in the span of {A, B, C}, so the given polynomials do not span P. When a 4, the three polynomials do span: A = (x )(x 1), B = (x )(x 4), C = x ax+4 = (x ) +(4 a), A + B 3C = 3(a 4), Since 3(a 4) is non-zero, 1 lies in Span{A, B, C}. Then D = x 3x = A (1) and E = x 6x = B 8(1) lie in Span{A, B, C}. Then D E = x and 1 (D E) lie in Span{A, B, C}. 3 Since 1, x and x lie in Span{A, B, C} and since Span{1, x, x } = P, we see that Span{A, B, C} = P, whenever a 4.

Question 6 Let A, B, C and D be the following matrices: A = 1 0 1, B = 1 3 1, C = 3 4 1, D = 1 3 1 4. Prove that A, B, C and D are linearly dependent and find a non-trivial linear relation between them. We solve the system: xa + yb + zc + td = 0, 0 0 0 0 = We reduce as follows: 1 1 0 1 3 3 3 4 1 1 1 1 4 x y + z + t y 3z + 3t x 3y + 4z t x y z + 4t. 1 1 0 1 3 3 0 1 3 3 1 1 0 1 3 3 0 0 0 0 1 1 0 0 3 6 0 0 0 0 The reduced system is: 1 0 0 1 0 0 1 0 0 0 0 1 0 5 0 0 3 6 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 1 0 5 0 0 1 0 0 0 0. x t = 0, y 3t = 0, z t = 0. We pick t = s and then [x, y, z, t] = s[1, 3,, 1], with s arbitrary. Picking s = 1, we have the non-trivial relation, showing that the set of matrices {A, B, C, D} is a linearly dependent set: A + 3B + C + D = 0. Also note that D = A 3B C. So the span of {A, B, C, D} equals the span of {A, B, C}.

Write down a set of four linearly independent matrices that together span all of M. A standard such set is {E, F, G, H}, where: E = 1 0 0 0, F = 0 1 0 0, G = 0 0 1 0, H = 0 0 0 1, xe + yf + zg + th = x y z t. The last equation shows that {E, F, G, H} spans M, since x, y, z and t are arbitrary. The same equation shows that if xe + yf + zg + th = 0, then x = y = z = t = 0. So the set of matrices {E, F, G, H} is a linearly independent set that spans M, as required. Hence, or otherwise, prove that the span of {A, B, C, D} cannot be all of M. If we suppose that {A, B, C, D} does span M, then each of E, F, G, H is expressible as as a linear combination of {A, B, C, D}. If we write the four linear systems for these linear combinations in one augmented matrix, we get the following augmented matrix Z : Z = 1 1 1 0 0 0 0 1 3 3 0 1 0 0 3 4 1 0 0 1 0 1 1 1 4 0 0 0 1 But this is also the augmented matrix for the linear system Y X = I, with coefficient matrix Y the matrix given by the first four columns of Z. If a solution X exists, then det(y ) det(x) = 1, so det(y ) 0 and Y is invertible. But we reduced the matrix Y above to a matrix with one zero row. So Y has no inverse and the solution X cannot exist. So at least one of the matrices E, F, G, H does not lie in Span{A, B, C, D}, so Span{A, B, C, D} M, as required.

Alternatively we may notice that for each of the matrices A, B, C and D, the sum of the (11) entry and the (1) entry always equals the () entry. Then any matrix in their span must have the same property. Since not every matrix has that property, they cannot span all of M. For example the following matrix does not have the property, so does not lie in Span{A, B, C, D}: 1 1 1 1