MA 1B PRACTICAL - HOMEWORK SET 3 SOLUTIONS. Solution. (d) We have matrix form Ax = b and vector equation 4

Similar documents
Lecture 2 Systems of Linear Equations and Matrices, Continued

Section 1.2. Row Reduction and Echelon Forms

1 Last time: linear systems and row operations

MATH 54 - WORKSHEET 1 MONDAY 6/22

Matrices, Row Reduction of Matrices

7.5 Operations with Matrices. Copyright Cengage Learning. All rights reserved.

Lecture 12: Solving Systems of Linear Equations by Gaussian Elimination

The matrix will only be consistent if the last entry of row three is 0, meaning 2b 3 + b 2 b 1 = 0.

Solving Linear Systems Using Gaussian Elimination

Lecture 3: Gaussian Elimination, continued. Lecture 3: Gaussian Elimination, continued

Chapter 1. Vectors, Matrices, and Linear Spaces

Homework 1.1 and 1.2 WITH SOLUTIONS

Linear Equations in Linear Algebra

Matrix equation Ax = b

Matrices and Systems of Equations

22A-2 SUMMER 2014 LECTURE 5

Notes on Row Reduction

Solving Consistent Linear Systems

Math 3C Lecture 20. John Douglas Moore

Exercise Sketch these lines and find their intersection.

Row Reduction and Echelon Forms

Lecture 4: Gaussian Elimination and Homogeneous Equations

Math 1314 Week #14 Notes

EBG # 3 Using Gaussian Elimination (Echelon Form) Gaussian Elimination: 0s below the main diagonal

4.3 Row operations. As we have seen in Section 4.1 we can simplify a system of equations by either:

5x 2 = 10. x 1 + 7(2) = 4. x 1 3x 2 = 4. 3x 1 + 9x 2 = 8

Announcements Wednesday, August 30

0.0.1 Section 1.2: Row Reduction and Echelon Forms Echelon form (or row echelon form): 1. All nonzero rows are above any rows of all zeros.

Midterm 1 Review. Written by Victoria Kala SH 6432u Office Hours: R 12:30 1:30 pm Last updated 10/10/2015

MODEL ANSWERS TO THE THIRD HOMEWORK

4 Elementary matrices, continued

13. Systems of Linear Equations 1

SOLVING Ax = b: GAUSS-JORDAN ELIMINATION [LARSON 1.2]

Chapter 4. Solving Systems of Equations. Chapter 4

Section Gaussian Elimination

4 Elementary matrices, continued

Connor Ahlbach Math 308 Notes

Elimination Method Streamlined

Solution: By inspection, the standard matrix of T is: A = Where, Ae 1 = 3. , and Ae 3 = 4. , Ae 2 =

1 - Systems of Linear Equations

Lectures on Linear Algebra for IT

Announcements Wednesday, August 30

Lecture 2e Row Echelon Form (pages 73-74)

Methods for Solving Linear Systems Part 2

Linear Algebra Math 221

Chapter 1: Systems of linear equations and matrices. Section 1.1: Introduction to systems of linear equations

Elementary matrices, continued. To summarize, we have identified 3 types of row operations and their corresponding

Math 54 HW 4 solutions

Chapter 2: Approximating Solutions of Linear Systems

Lecture 6 & 7. Shuanglin Shao. September 16th and 18th, 2013

Chapter 2. Systems of Equations and Augmented Matrices. Creighton University

Find the solution set of 2x 3y = 5. Answer: We solve for x = (5 + 3y)/2. Hence the solution space consists of all vectors of the form

M 340L CS Homework Set 1

Lecture 1 Systems of Linear Equations and Matrices

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

Linear Algebra I Lecture 10

Solving Systems of Linear Equations Using Matrices

And, even if it is square, we may not be able to use EROs to get to the identity matrix. Consider

Example: 2x y + 3z = 1 5y 6z = 0 x + 4z = 7. Definition: Elementary Row Operations. Example: Type I swap rows 1 and 3

Section Gauss Elimination for Systems of Linear Equations

Math 2331 Linear Algebra

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:

Math 54 Homework 3 Solutions 9/

R2 R2 2R R2 R1 3R This is the reduced echelon form of our matrix. It corresponds to the linear system of equations

Pre-Calculus I. For example, the system. x y 2 z. may be represented by the augmented matrix

Finite Mathematics Chapter 2. where a, b, c, d, h, and k are real numbers and neither a and b nor c and d are both zero.

Handout 1 EXAMPLES OF SOLVING SYSTEMS OF LINEAR EQUATIONS

3. Replace any row by the sum of that row and a constant multiple of any other row.

Linear Equations in Linear Algebra

Relationships Between Planes

Matrix Factorization Reading: Lay 2.5

Section 5.3 Systems of Linear Equations: Determinants

Linear Algebra I Lecture 8

MA 242 LINEAR ALGEBRA C1, Solutions to First Midterm Exam

Matrices and RRE Form

Math 4A Notes. Written by Victoria Kala Last updated June 11, 2017

Linear Algebra Exam 1 Spring 2007

Elementary Matrices. MATH 322, Linear Algebra I. J. Robert Buchanan. Spring Department of Mathematics

1.4 Gaussian Elimination Gaussian elimination: an algorithm for finding a (actually the ) reduced row echelon form of a matrix. A row echelon form

Systems of Equations Homework Solutions

Topics. Vectors (column matrices): Vector addition and scalar multiplication The matrix of a linear function y Ax The elements of a matrix A : A ij

MAC1105-College Algebra. Chapter 5-Systems of Equations & Matrices

Math 344 Lecture # Linear Systems

Row Reduced Echelon Form

MTH 2530: Linear Algebra. Sec Systems of Linear Equations

Chapter 1: Systems of Linear Equations

The Gauss-Jordan Elimination Algorithm

EXAM. Exam #3. Math 2360 Fall 2000 Morning Class. Nov. 29, 2000 ANSWERS

Solutions of Linear system, vector and matrix equation

System of Linear Equations

Math 2331 Linear Algebra

Linear Methods (Math 211) - Lecture 2

MATH10212 Linear Algebra B Homework Week 4

Sections 6.1 and 6.2: Systems of Linear Equations

Lecture 7: Introduction to linear systems

Linear Equations in Linear Algebra

40h + 15c = c = h

MATH 2050 Assignment 6 Fall 2018 Due: Thursday, November 1. x + y + 2z = 2 x + y + z = c 4x + 2z = 2

Section 2.2: The Inverse of a Matrix

Problem Sheet 1 with Solutions GRA 6035 Mathematics

Transcription:

MA B PRACTICAL - HOMEWORK SET SOLUTIONS (Reading) ( pts)[ch, Problem (d), (e)] Solution (d) We have matrix form Ax = b and vector equation 4 i= x iv i = b, where v i is the ith column of A, and 4 A = 8 4, b = 4 5 We perform row reduction Using the first row to clear the first column of the other two rows, we get the augmented matrix 4 6 6 Now the last two rows are multiples of each other, so we can eliminate the third row, factor a constant out of the second row, and then add the second row to the first row to arrive at 4 4 Here we take x and x 4 as free variables, whence x = 4+4x +x 4 and x = +x 4 Hence the solution set is, in vector form 4 4 x = + x + x 4 (e) We have matrix form Ax = b and vector equation 4 i= x iv i = b, where v i is the ith column of A, and A = 4 6, b = 5 We again perform row reduction, using the first row to clear the first entry in the second row: 9 6 Date: January, 7

MA B PRACTICAL - HOMEWORK SET SOLUTIONS Swapping the last two rows places the augmented matrix in row echelon form:, and a few more operations leave our augmented matrix in reduced row echelon form: Here x 4 is free, and x = +x 4, x = x 4, x = In vector form, the solution is x = + x 4 ( pts) Find a basis of each of the following vector spaces: (a) {(x, x,, x n ) T F n x + x + + x n = nx n } (b) {(x, x, x, x 4, x 5 ) T F 5 x = x, x = 7x 4, x + x + x 5 = } Solution (a) If n =, then our vector space is just F, and F is a single-element basis If n >, then for any (x,, x n ) in the space, we must have x n = (x + x + + x n )/(n ) Thus we can take x, x n as free variables So we have a basis {(,,,, (n ) ) T, (,,,, (n ) ) T,, (,,,, (n ) ) T } (b) We can rewrite the condition as 7 x = Row reduction leads to the following equivalent system: /4 /4 x = 7 We can thus take x 4 and x 5 as free variables, with x = x 5 /4, x = x 5 /4, and x = 7x 4 So we have the following basis for our vector space: {(,, 7,, ) T, ( /4, /4,,, ) T } 4 ( pts)[ch, Problem ] For what value of b does the system x 4 6 x = 4 x b have a solution Find the general solution of this system for this value of b

MA B PRACTICAL - HOMEWORK SET SOLUTIONS Solution To solve this, we will begin by determining the augmented matrix for our system of equations: 4 6 4 b We now attempt to put this matrix into echelon form First, simply because it is easier to do it this way, we subtract half the second row from the third row to obtain 4 6 4 b Finally, although not strictly necessary for this problem, we complete the reduction into row echelon form by dividing the second row by two and then subtracting the first row from it The result of this process is the augmented matrix b Recall now that a system is inconsistent if and only if there is a pivot in the last column of an echelon form of the augmented matrix Thus, in particular, we have that the system under consideration is inconsistent if and only if b Thus the unique value of b for which our system of equations has a solution is b = We now begin the process of finding a solution Take b = Then we have the system x x + x + x 4 6 x = x + 4x + 6x = 4 x x + x + x Note that the last and second to last conditions are saying the same thing, so in fact we have two linear equations in three unknowns, namely, x + x + x = and x + x + x = Subtracting the first condition from the second one, we immediately see that x = Now, this, in fact renders the two above equations into the same one, namely x + x =, or, rearranging, x = x + Thus, the general form of the solution to this equation is x x = x x x+ 5 ( pts)[ch Problem 4] Find the inverse of the matrices A = 7, B = 4 4 Show all steps

4 MA B PRACTICAL - HOMEWORK SET SOLUTIONS Solution We will find the inverses of these matrices via row reduction First we turn our attention to A We begin by forming (A I) We get 7 4 We begin by subtracting thrice the first row from the second row, since we note that this will yield ( ), which results in 4 We continue by subtracting twice the first row from the third, in order to clear out the left-most zero from the third column: We then clear out the second zero in the bottom row by adding row to row : 5 Now, we ensure that the leading coefficient in the bottom row is by dividing that row by to obtain 5 Now, we proceed to clear out the remainder of the top row We subtract row from row to obtain 7 5 Finally, we conclude by subtracting twice the second row from the first row to obtain 9 5 5 Thus, reading off the inverse, we see that 9 5 7 = 4 Now, we turn our attention to B We begin by forming (B I) We get 4 5

MA B PRACTICAL - HOMEWORK SET SOLUTIONS 5 We begin by clearing out the first position of the second row by subtracting row from row to obtain 4 4 Similarly, we subtract the first row from the third to obtain 4 We then clear out the second zero in the bottom row by subtracting row from row : 4 6 Now, we ensure that the leading coefficient in the bottom row is by dividing that row by 6 to obtain 4 We then add four times the final row to the second one to clear out the remaining nonzero term we wish to get rid of: We then divide the second row by to ensure that it is in the proper form: 6 Now, we begin our work on the top row We clear out the first lagging zero by subtracting off twice the last row to obtain 6 Finally, we add row to row to clear out the remaining lagging term: 6 Reading off the inverse, we obtain that = 6 = 4 6