Evaluating Determinants by Row Reduction

Size: px
Start display at page:

Download "Evaluating Determinants by Row Reduction"

Transcription

1 Evaluating Determinants by Row Reduction MATH 322, Linear Algebra I J. Robert Buchanan Department of Mathematics Spring 2015

2 Objectives Reduce a matrix to row echelon form and evaluate its determinant. Row reduction requires fewer operations than cofactor expansion and is therefore more efficient for large matrices.

3 Basic Theorems (1 of 2) Theorem Let A be a square matrix, if A has a row or column of zeros, then det(a) = 0.

4 Basic Theorems (1 of 2) Theorem Let A be a square matrix, if A has a row or column of zeros, then det(a) = 0. Proof. Suppose the ith row contains only zeros and perform cofactor expansion along the ith row. det(a) = (0)C i1 + (0)C i2 + + (0)C in = 0

5 Basic Theorems (2 of 2) Theorem Let A be a square matrix, then det(a) = det(a T ).

6 Basic Theorems (2 of 2) Theorem Let A be a square matrix, then det(a) = det(a T ). Proof. The ith row of A is the ith column of A T. Therefore cofactor expansion along the ith row of A is the same as cofactor expansion along the i column of A T.

7 Basic Theorems (2 of 2) Theorem Let A be a square matrix, then det(a) = det(a T ). Proof. The ith row of A is the ith column of A T. Therefore cofactor expansion along the ith row of A is the same as cofactor expansion along the i column of A T. Remark: rows vs. columns are irrelevant when talking about determinants.

8 Elementary Row Operations Questions: what effect do elementary row operations have on the calculation of the determinant?

9 Elementary Row Operations Questions: what effect do elementary row operations have on the calculation of the determinant? Theorem Let A be an n n matrix. 1. If B is the matrix that results when a single row or column of A is multiplied by a scalar k, then det(b) = k det(a). 2. If B is the matrix that results when two rows or columns of A are interchanged, then det(b) = det(a). 3. If B is the matrix that results when a multiple of one row of A is added to another row or when a multiple of one column is added to another column, then det(b) = det(a).

10 Illustrations for 3 3 Matrices ka 11 ka 12 ka 13 a 21 a 22 a 23 a 31 a 32 a 33 a 21 a 22 a 23 a 11 a 12 a 13 a 31 a 32 a 33 a 11 + ka 21 a 12 + ka 22 a 13 + ka 23 a 21 a 22 a 23 a 31 a 32 a 33 = k = = a 11 a 12 a 13 a 21 a 22 a 23 a 31 a 32 a 33 a 11 a 12 a 13 a 21 a 22 a 23 a 31 a 32 a 33 a 11 a 12 a 13 a 21 a 22 a 23 a 31 a 32 a 33

11 Proof (1) Suppose matrix B is the same as matrix A except that the ith row of B is the ith row of A multiplied by k.

12 Proof (1) Suppose matrix B is the same as matrix A except that the ith row of B is the ith row of A multiplied by k. Form the cofactor expansion of det(b) along the ith row. det(b) = ka i1 C i1 + ka i2 C i2 + + ka in C in = k(a i1 C i1 + a i2 C i2 + + a in C in )

13 Proof (1) Suppose matrix B is the same as matrix A except that the ith row of B is the ith row of A multiplied by k. Form the cofactor expansion of det(b) along the ith row. det(b) = ka i1 C i1 + ka i2 C i2 + + ka in C in = k(a i1 C i1 + a i2 C i2 + + a in C in ) = k det(a) since the cofactors C ij are independent of the entries in the i row.

14 Examples Let A = and calculate the following determinants = = =

15 Examples Let A = and calculate the following determinants = 92 = =

16 Examples Let A = and calculate the following determinants = 92 = 46 =

17 Examples Let A = and calculate the following determinants = 92 = 46 = 46

18 Elementary Matrices Recall: an elementary matrix results from applying a single elementary row operation to the identity matrix.

19 Elementary Matrices Recall: an elementary matrix results from applying a single elementary row operation to the identity matrix. Theorem Let E be an n n elementary matrix. 1. If E is the matrix that results from multiplying a row of I n by a scalar k, then det(e) = k. 2. If E is the matrix that results when two rows I n are interchanged, then det(e) = If E is the matrix that results when a multiple of one row of I n is added to another row, then det(e) = 1.

20 Elementary Matrices Recall: an elementary matrix results from applying a single elementary row operation to the identity matrix. Theorem Let E be an n n elementary matrix. 1. If E is the matrix that results from multiplying a row of I n by a scalar k, then det(e) = k. 2. If E is the matrix that results when two rows I n are interchanged, then det(e) = If E is the matrix that results when a multiple of one row of I n is added to another row, then det(e) = 1. Proof. det(i n ) = 1

21 Examples Evaluate the following determinants of elementary matrices = = =

22 Examples Evaluate the following determinants of elementary matrices = = =

23 Examples Evaluate the following determinants of elementary matrices = = =

24 Examples Evaluate the following determinants of elementary matrices = = =

25 Proportional Rows of Columns Theorem If A is an n n matrix with two proportional rows or columns, then det(a) = 0.

26 Proportional Rows of Columns Theorem If A is an n n matrix with two proportional rows or columns, then det(a) = 0. Proof. If the ith row is k times jth row, then multiply the jth row j by k and add to the ith row. This elementary row operation does not change the determinant of A. Now A has a row of zeros and thus det(a) = 0.

27 Examples Find the determinants of the following matrices

28 Row Reduction If we row-reduce a matrix to upper triangular form we can then easily calculate its determinant. Example Evaluate the following determinant

29 Homework Read Section 2.2 Exercises: 1 29 odd

Properties of the Determinant Function

Properties of the Determinant Function Properties of the Determinant Function MATH 322, Linear Algebra I J. Robert Buchanan Department of Mathematics Spring 2015 Overview Today s discussion will illuminate some of the properties of the determinant:

More information

Chapter 2:Determinants. Section 2.1: Determinants by cofactor expansion

Chapter 2:Determinants. Section 2.1: Determinants by cofactor expansion Chapter 2:Determinants Section 2.1: Determinants by cofactor expansion [ ] a b Recall: The 2 2 matrix is invertible if ad bc 0. The c d ([ ]) a b function f = ad bc is called the determinant and it associates

More information

Row Space, Column Space, and Nullspace

Row Space, Column Space, and Nullspace Row Space, Column Space, and Nullspace MATH 322, Linear Algebra I J. Robert Buchanan Department of Mathematics Spring 2015 Introduction Every matrix has associated with it three vector spaces: row space

More information

MATH 2050 Assignment 8 Fall [10] 1. Find the determinant by reducing to triangular form for the following matrices.

MATH 2050 Assignment 8 Fall [10] 1. Find the determinant by reducing to triangular form for the following matrices. MATH 2050 Assignment 8 Fall 2016 [10] 1. Find the determinant by reducing to triangular form for the following matrices. 0 1 2 (a) A = 2 1 4. ANS: We perform the Gaussian Elimination on A by the following

More information

Determinants by Cofactor Expansion (III)

Determinants by Cofactor Expansion (III) Determinants by Cofactor Expansion (III) Comment: (Reminder) If A is an n n matrix, then the determinant of A can be computed as a cofactor expansion along the jth column det(a) = a1j C1j + a2j C2j +...

More information

Properties of Linear Transformations from R n to R m

Properties of Linear Transformations from R n to R m Properties of Linear Transformations from R n to R m MATH 322, Linear Algebra I J. Robert Buchanan Department of Mathematics Spring 2015 Topic Overview Relationship between the properties of a matrix transformation

More information

Determinants Chapter 3 of Lay

Determinants Chapter 3 of Lay Determinants Chapter of Lay Dr. Doreen De Leon Math 152, Fall 201 1 Introduction to Determinants Section.1 of Lay Given a square matrix A = [a ij, the determinant of A is denoted by det A or a 11 a 1j

More information

Components and change of basis

Components and change of basis Math 20F Linear Algebra Lecture 16 1 Components and change of basis Slide 1 Review: Isomorphism Review: Components in a basis Unique representation in a basis Change of basis Review: Isomorphism Definition

More information

Chapter 4. Determinants

Chapter 4. Determinants 4.2 The Determinant of a Square Matrix 1 Chapter 4. Determinants 4.2 The Determinant of a Square Matrix Note. In this section we define the determinant of an n n matrix. We will do so recursively by defining

More information

Formula for the inverse matrix. Cramer s rule. Review: 3 3 determinants can be computed expanding by any row or column

Formula for the inverse matrix. Cramer s rule. Review: 3 3 determinants can be computed expanding by any row or column Math 20F Linear Algebra Lecture 18 1 Determinants, n n Review: The 3 3 case Slide 1 Determinants n n (Expansions by rows and columns Relation with Gauss elimination matrices: Properties) Formula for the

More information

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

Elementary Matrices. MATH 322, Linear Algebra I. J. Robert Buchanan. Spring Department of Mathematics Elementary Matrices MATH 322, Linear Algebra I J. Robert Buchanan Department of Mathematics Spring 2015 Outline Today s discussion will focus on: elementary matrices and their properties, using elementary

More information

Linear Algebra and Vector Analysis MATH 1120

Linear Algebra and Vector Analysis MATH 1120 Faculty of Engineering Mechanical Engineering Department Linear Algebra and Vector Analysis MATH 1120 : Instructor Dr. O. Philips Agboola Determinants and Cramer s Rule Determinants If a matrix is square

More information

Determinants. Samy Tindel. Purdue University. Differential equations and linear algebra - MA 262

Determinants. Samy Tindel. Purdue University. Differential equations and linear algebra - MA 262 Determinants Samy Tindel Purdue University Differential equations and linear algebra - MA 262 Taken from Differential equations and linear algebra by Goode and Annin Samy T. Determinants Differential equations

More information

MATH 1210 Assignment 4 Solutions 16R-T1

MATH 1210 Assignment 4 Solutions 16R-T1 MATH 1210 Assignment 4 Solutions 16R-T1 Attempt all questions and show all your work. Due November 13, 2015. 1. Prove using mathematical induction that for any n 2, and collection of n m m matrices A 1,

More information

4. Determinants.

4. Determinants. 4. Determinants 4.1. Determinants; Cofactor Expansion Determinants of 2 2 and 3 3 Matrices 2 2 determinant 4.1. Determinants; Cofactor Expansion Determinants of 2 2 and 3 3 Matrices 3 3 determinant 4.1.

More information

Determinants. Recall that the 2 2 matrix a b c d. is invertible if

Determinants. Recall that the 2 2 matrix a b c d. is invertible if Determinants Recall that the 2 2 matrix a b c d is invertible if and only if the quantity ad bc is nonzero. Since this quantity helps to determine the invertibility of the matrix, we call it the determinant.

More information

ECON 186 Class Notes: Linear Algebra

ECON 186 Class Notes: Linear Algebra ECON 86 Class Notes: Linear Algebra Jijian Fan Jijian Fan ECON 86 / 27 Singularity and Rank As discussed previously, squareness is a necessary condition for a matrix to be nonsingular (have an inverse).

More information

Linear Systems and Matrices

Linear Systems and Matrices Department of Mathematics The Chinese University of Hong Kong 1 System of m linear equations in n unknowns (linear system) a 11 x 1 + a 12 x 2 + + a 1n x n = b 1 a 21 x 1 + a 22 x 2 + + a 2n x n = b 2.......

More information

Linear Algebra: Lecture notes from Kolman and Hill 9th edition.

Linear Algebra: Lecture notes from Kolman and Hill 9th edition. Linear Algebra: Lecture notes from Kolman and Hill 9th edition Taylan Şengül March 20, 2019 Please let me know of any mistakes in these notes Contents Week 1 1 11 Systems of Linear Equations 1 12 Matrices

More information

Determinant: 3.2 Evaluation of Determinant with Elementary

Determinant: 3.2 Evaluation of Determinant with Elementary Determinant: 3.2 Evaluation of Determinant with Elementary Operations September 18 As far as the laws of mathematics refer to reality, they are not certain; and as far as they are certain, they do not

More information

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

MATH Topics in Applied Mathematics Lecture 12: Evaluation of determinants. Cross product. MATH 311-504 Topics in Applied Mathematics Lecture 12: Evaluation of determinants. Cross product. Determinant is a scalar assigned to each square matrix. Notation. The determinant of a matrix A = (a ij

More information

Math 240 Calculus III

Math 240 Calculus III The Calculus III Summer 2015, Session II Wednesday, July 8, 2015 Agenda 1. of the determinant 2. determinants 3. of determinants What is the determinant? Yesterday: Ax = b has a unique solution when A

More information

k=1 ( 1)k+j M kj detm kj. detm = ad bc. = 1 ( ) 2 ( )+3 ( ) = = 0

k=1 ( 1)k+j M kj detm kj. detm = ad bc. = 1 ( ) 2 ( )+3 ( ) = = 0 4 Determinants The determinant of a square matrix is a scalar (i.e. an element of the field from which the matrix entries are drawn which can be associated to it, and which contains a surprisingly large

More information

Math Linear Algebra Final Exam Review Sheet

Math Linear Algebra Final Exam Review Sheet Math 15-1 Linear Algebra Final Exam Review Sheet Vector Operations Vector addition is a component-wise operation. Two vectors v and w may be added together as long as they contain the same number n of

More information

MATH 323 Linear Algebra Lecture 6: Matrix algebra (continued). Determinants.

MATH 323 Linear Algebra Lecture 6: Matrix algebra (continued). Determinants. MATH 323 Linear Algebra Lecture 6: Matrix algebra (continued). Determinants. Elementary matrices Theorem 1 Any elementary row operation σ on matrices with n rows can be simulated as left multiplication

More information

Chapter 3. Determinants and Eigenvalues

Chapter 3. Determinants and Eigenvalues Chapter 3. Determinants and Eigenvalues 3.1. Determinants With each square matrix we can associate a real number called the determinant of the matrix. Determinants have important applications to the theory

More information

Elementary Matrices. which is obtained by multiplying the first row of I 3 by -1, and

Elementary Matrices. which is obtained by multiplying the first row of I 3 by -1, and Elementary Matrices In this special handout of material not contained in the text, we introduce the concept of elementary matrix. Elementary matrices are useful in several ways that will be shown in this

More information

Matrix Algebra Determinant, Inverse matrix. Matrices. A. Fabretti. Mathematics 2 A.Y. 2015/2016. A. Fabretti Matrices

Matrix Algebra Determinant, Inverse matrix. Matrices. A. Fabretti. Mathematics 2 A.Y. 2015/2016. A. Fabretti Matrices Matrices A. Fabretti Mathematics 2 A.Y. 2015/2016 Table of contents Matrix Algebra Determinant Inverse Matrix Introduction A matrix is a rectangular array of numbers. The size of a matrix is indicated

More information

MAC Module 3 Determinants. Learning Objectives. Upon completing this module, you should be able to:

MAC Module 3 Determinants. Learning Objectives. Upon completing this module, you should be able to: MAC 2 Module Determinants Learning Objectives Upon completing this module, you should be able to:. Determine the minor, cofactor, and adjoint of a matrix. 2. Evaluate the determinant of a matrix by cofactor

More information

Chapter 2. Square matrices

Chapter 2. Square matrices Chapter 2. Square matrices Lecture notes for MA1111 P. Karageorgis pete@maths.tcd.ie 1/18 Invertible matrices Definition 2.1 Invertible matrices An n n matrix A is said to be invertible, if there is a

More information

Matrices. In this chapter: matrices, determinants. inverse matrix

Matrices. In this chapter: matrices, determinants. inverse matrix Matrices In this chapter: matrices, determinants inverse matrix 1 1.1 Matrices A matrix is a retangular array of numbers. Rows: horizontal lines. A = a 11 a 12 a 13 a 21 a 22 a 23 a 31 a 32 a 33 a 41 a

More information

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

7.5 Operations with Matrices. Copyright Cengage Learning. All rights reserved. 7.5 Operations with Matrices Copyright Cengage Learning. All rights reserved. What You Should Learn Decide whether two matrices are equal. Add and subtract matrices and multiply matrices by scalars. Multiply

More information

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

Diagonalization. MATH 322, Linear Algebra I. J. Robert Buchanan. Spring Department of Mathematics Diagonalization MATH 322, Linear Algebra I J. Robert Buchanan Department of Mathematics Spring 2015 Motivation Today we consider two fundamental questions: Given an n n matrix A, does there exist a basis

More information

Graduate Mathematical Economics Lecture 1

Graduate Mathematical Economics Lecture 1 Graduate Mathematical Economics Lecture 1 Yu Ren WISE, Xiamen University September 23, 2012 Outline 1 2 Course Outline ematical techniques used in graduate level economics courses Mathematics for Economists

More information

det(ka) = k n det A.

det(ka) = k n det A. Properties of determinants Theorem. If A is n n, then for any k, det(ka) = k n det A. Multiplying one row of A by k multiplies the determinant by k. But ka has every row multiplied by k, so the determinant

More information

Chapter 1. Vectors, Matrices, and Linear Spaces

Chapter 1. Vectors, Matrices, and Linear Spaces 1.4 Solving Systems of Linear Equations 1 Chapter 1. Vectors, Matrices, and Linear Spaces 1.4. Solving Systems of Linear Equations Note. We give an algorithm for solving a system of linear equations (called

More information

Determinants and Scalar Multiplication

Determinants and Scalar Multiplication Properties of Determinants In the last section, we saw how determinants interact with the elementary row operations. There are other operations on matrices, though, such as scalar multiplication, matrix

More information

Kevin James. MTHSC 3110 Section 2.2 Inverses of Matrices

Kevin James. MTHSC 3110 Section 2.2 Inverses of Matrices MTHSC 3110 Section 2.2 Inverses of Matrices Definition Suppose that T : R n R m is linear. We will say that T is invertible if for every b R m there is exactly one x R n so that T ( x) = b. Note If T is

More information

Matrix Algebra. Matrix Algebra. Chapter 8 - S&B

Matrix Algebra. Matrix Algebra. Chapter 8 - S&B Chapter 8 - S&B Algebraic operations Matrix: The size of a matrix is indicated by the number of its rows and the number of its columns. A matrix with k rows and n columns is called a k n matrix. The number

More information

Math 3C Lecture 20. John Douglas Moore

Math 3C Lecture 20. John Douglas Moore Math 3C Lecture 20 John Douglas Moore May 18, 2009 TENTATIVE FORMULA I Midterm I: 20% Midterm II: 20% Homework: 10% Quizzes: 10% Final: 40% TENTATIVE FORMULA II Higher of two midterms: 30% Homework: 10%

More information

SPRING OF 2008 D. DETERMINANTS

SPRING OF 2008 D. DETERMINANTS 18024 SPRING OF 2008 D DETERMINANTS In many applications of linear algebra to calculus and geometry, the concept of a determinant plays an important role This chapter studies the basic properties of determinants

More information

Question: Given an n x n matrix A, how do we find its eigenvalues? Idea: Suppose c is an eigenvalue of A, then what is the determinant of A-cI?

Question: Given an n x n matrix A, how do we find its eigenvalues? Idea: Suppose c is an eigenvalue of A, then what is the determinant of A-cI? Section 5. The Characteristic Polynomial Question: Given an n x n matrix A, how do we find its eigenvalues? Idea: Suppose c is an eigenvalue of A, then what is the determinant of A-cI? Property The eigenvalues

More information

Calculating determinants for larger matrices

Calculating determinants for larger matrices Day 26 Calculating determinants for larger matrices We now proceed to define det A for n n matrices A As before, we are looking for a function of A that satisfies the product formula det(ab) = det A det

More information

Math Camp Notes: Linear Algebra I

Math Camp Notes: Linear Algebra I Math Camp Notes: Linear Algebra I Basic Matrix Operations and Properties Consider two n m matrices: a a m A = a n a nm Then the basic matrix operations are as follows: a + b a m + b m A + B = a n + b n

More information

II. Determinant Functions

II. Determinant Functions Supplemental Materials for EE203001 Students II Determinant Functions Chung-Chin Lu Department of Electrical Engineering National Tsing Hua University May 22, 2003 1 Three Axioms for a Determinant Function

More information

Lemma 8: Suppose the N by N matrix A has the following block upper triangular form:

Lemma 8: Suppose the N by N matrix A has the following block upper triangular form: 17 4 Determinants and the Inverse of a Square Matrix In this section, we are going to use our knowledge of determinants and their properties to derive an explicit formula for the inverse of a square matrix

More information

Determinants: Elementary Row/Column Operations

Determinants: Elementary Row/Column Operations Determinants: Elementary Row/Column Operations Linear Algebra Josh Engwer TTU 23 September 2015 Josh Engwer (TTU) Determinants: Elementary Row/Column Operations 23 September 2015 1 / 16 Elementary Row

More information

Homework Set #8 Solutions

Homework Set #8 Solutions Exercises.2 (p. 19) Homework Set #8 Solutions Assignment: Do #6, 8, 12, 14, 2, 24, 26, 29, 0, 2, 4, 5, 6, 9, 40, 42 6. Reducing the matrix to echelon form: 1 5 2 1 R2 R2 R1 1 5 0 18 12 2 1 R R 2R1 1 5

More information

System of Linear Equations

System of Linear Equations Math 20F Linear Algebra Lecture 2 1 System of Linear Equations Slide 1 Definition 1 Fix a set of numbers a ij, b i, where i = 1,, m and j = 1,, n A system of m linear equations in n variables x j, is given

More information

Linear Algebra. Matrices Operations. Consider, for example, a system of equations such as x + 2y z + 4w = 0, 3x 4y + 2z 6w = 0, x 3y 2z + w = 0.

Linear Algebra. Matrices Operations. Consider, for example, a system of equations such as x + 2y z + 4w = 0, 3x 4y + 2z 6w = 0, x 3y 2z + w = 0. Matrices Operations Linear Algebra Consider, for example, a system of equations such as x + 2y z + 4w = 0, 3x 4y + 2z 6w = 0, x 3y 2z + w = 0 The rectangular array 1 2 1 4 3 4 2 6 1 3 2 1 in which the

More information

Undergraduate Mathematical Economics Lecture 1

Undergraduate Mathematical Economics Lecture 1 Undergraduate Mathematical Economics Lecture 1 Yu Ren WISE, Xiamen University September 15, 2014 Outline 1 Courses Description and Requirement 2 Course Outline ematical techniques used in economics courses

More information

MATH 2030: EIGENVALUES AND EIGENVECTORS

MATH 2030: EIGENVALUES AND EIGENVECTORS MATH 2030: EIGENVALUES AND EIGENVECTORS Determinants Although we are introducing determinants in the context of matrices, the theory of determinants predates matrices by at least two hundred years Their

More information

Algebra & Trig. I. For example, the system. x y 2 z. may be represented by the augmented matrix

Algebra & Trig. I. For example, the system. x y 2 z. may be represented by the augmented matrix Algebra & Trig. I 8.1 Matrix Solutions to Linear Systems A matrix is a rectangular array of elements. o An array is a systematic arrangement of numbers or symbols in rows and columns. Matrices (the plural

More information

Review for Exam Find all a for which the following linear system has no solutions, one solution, and infinitely many solutions.

Review for Exam Find all a for which the following linear system has no solutions, one solution, and infinitely many solutions. Review for Exam. Find all a for which the following linear system has no solutions, one solution, and infinitely many solutions. x + y z = 2 x + 2y + z = 3 x + y + (a 2 5)z = a 2 The augmented matrix for

More information

A = , A 32 = n ( 1) i +j a i j det(a i j). (1) j=1

A = , A 32 = n ( 1) i +j a i j det(a i j). (1) j=1 Lecture Notes: Determinant of a Square Matrix Yufei Tao Department of Computer Science and Engineering Chinese University of Hong Kong taoyf@cse.cuhk.edu.hk 1 Determinant Definition Let A [a ij ] be an

More information

3 Matrix Algebra. 3.1 Operations on matrices

3 Matrix Algebra. 3.1 Operations on matrices 3 Matrix Algebra A matrix is a rectangular array of numbers; it is of size m n if it has m rows and n columns. A 1 n matrix is a row vector; an m 1 matrix is a column vector. For example: 1 5 3 5 3 5 8

More information

Chapter 4 - MATRIX ALGEBRA. ... a 2j... a 2n. a i1 a i2... a ij... a in

Chapter 4 - MATRIX ALGEBRA. ... a 2j... a 2n. a i1 a i2... a ij... a in Chapter 4 - MATRIX ALGEBRA 4.1. Matrix Operations A a 11 a 12... a 1j... a 1n a 21. a 22.... a 2j... a 2n. a i1 a i2... a ij... a in... a m1 a m2... a mj... a mn The entry in the ith row and the jth column

More information

7.3. Determinants. Introduction. Prerequisites. Learning Outcomes

7.3. Determinants. Introduction. Prerequisites. Learning Outcomes Determinants 7.3 Introduction Among other uses, determinants allow us to determine whether a system of linear equations has a unique solution or not. The evaluation of a determinant is a key skill in engineering

More information

MATH2210 Notebook 2 Spring 2018

MATH2210 Notebook 2 Spring 2018 MATH2210 Notebook 2 Spring 2018 prepared by Professor Jenny Baglivo c Copyright 2009 2018 by Jenny A. Baglivo. All Rights Reserved. 2 MATH2210 Notebook 2 3 2.1 Matrices and Their Operations................................

More information

Section 1.1 System of Linear Equations. Dr. Abdulla Eid. College of Science. MATHS 211: Linear Algebra

Section 1.1 System of Linear Equations. Dr. Abdulla Eid. College of Science. MATHS 211: Linear Algebra Section 1.1 System of Linear Equations College of Science MATHS 211: Linear Algebra (University of Bahrain) Linear System 1 / 33 Goals:. 1 Define system of linear equations and their solutions. 2 To represent

More information

1300 Linear Algebra and Vector Geometry

1300 Linear Algebra and Vector Geometry 1300 Linear Algebra and Vector Geometry R. Craigen Office: MH 523 Email: craigenr@umanitoba.ca May-June 2017 Matrix Inversion Algorithm One payoff from this theorem: It gives us a way to invert matrices.

More information

Math 4377/6308 Advanced Linear Algebra

Math 4377/6308 Advanced Linear Algebra 3.1 Elementary Matrix Math 4377/6308 Advanced Linear Algebra 3.1 Elementary Matrix Operations and Elementary Matrix Jiwen He Department of Mathematics, University of Houston jiwenhe@math.uh.edu math.uh.edu/

More information

Rank and Nullity. MATH 322, Linear Algebra I. J. Robert Buchanan. Spring Department of Mathematics

Rank and Nullity. MATH 322, Linear Algebra I. J. Robert Buchanan. Spring Department of Mathematics Rank and Nullity MATH 322, Linear Algebra I J. Robert Buchanan Department of Mathematics Spring 2015 Objectives We have defined and studied the important vector spaces associated with matrices (row space,

More information

Materials engineering Collage \\ Ceramic & construction materials department Numerical Analysis \\Third stage by \\ Dalya Hekmat

Materials engineering Collage \\ Ceramic & construction materials department Numerical Analysis \\Third stage by \\ Dalya Hekmat Materials engineering Collage \\ Ceramic & construction materials department Numerical Analysis \\Third stage by \\ Dalya Hekmat Linear Algebra Lecture 2 1.3.7 Matrix Matrix multiplication using Falk s

More information

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

Elementary matrices, continued. To summarize, we have identified 3 types of row operations and their corresponding Elementary matrices, continued To summarize, we have identified 3 types of row operations and their corresponding elementary matrices. If you check the previous examples, you ll find that these matrices

More information

and let s calculate the image of some vectors under the transformation T.

and let s calculate the image of some vectors under the transformation T. Chapter 5 Eigenvalues and Eigenvectors 5. Eigenvalues and Eigenvectors Let T : R n R n be a linear transformation. Then T can be represented by a matrix (the standard matrix), and we can write T ( v) =

More information

Introduction. Vectors and Matrices. Vectors [1] Vectors [2]

Introduction. Vectors and Matrices. Vectors [1] Vectors [2] Introduction Vectors and Matrices Dr. TGI Fernando 1 2 Data is frequently arranged in arrays, that is, sets whose elements are indexed by one or more subscripts. Vector - one dimensional array Matrix -

More information

MATH 240 Spring, Chapter 1: Linear Equations and Matrices

MATH 240 Spring, Chapter 1: Linear Equations and Matrices MATH 240 Spring, 2006 Chapter Summaries for Kolman / Hill, Elementary Linear Algebra, 8th Ed. Sections 1.1 1.6, 2.1 2.2, 3.2 3.8, 4.3 4.5, 5.1 5.3, 5.5, 6.1 6.5, 7.1 7.2, 7.4 DEFINITIONS Chapter 1: Linear

More information

Numerical Linear Algebra Homework Assignment - Week 2

Numerical Linear Algebra Homework Assignment - Week 2 Numerical Linear Algebra Homework Assignment - Week 2 Đoàn Trần Nguyên Tùng Student ID: 1411352 8th October 2016 Exercise 2.1: Show that if a matrix A is both triangular and unitary, then it is diagonal.

More information

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

MATH 213 Linear Algebra and ODEs Spring 2015 Study Sheet for Midterm Exam. Topics MATH 213 Linear Algebra and ODEs Spring 2015 Study Sheet for Midterm Exam This study sheet will not be allowed during the test Books and notes will not be allowed during the test Calculators and cell phones

More information

Math 304 Fall 2018 Exam 3 Solutions 1. (18 Points, 3 Pts each part) Let A, B, C, D be square matrices of the same size such that

Math 304 Fall 2018 Exam 3 Solutions 1. (18 Points, 3 Pts each part) Let A, B, C, D be square matrices of the same size such that Math 304 Fall 2018 Exam 3 Solutions 1. (18 Points, 3 Pts each part) Let A, B, C, D be square matrices of the same size such that det(a) = 2, det(b) = 2, det(c) = 1, det(d) = 4. 2 (a) Compute det(ad)+det((b

More information

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

2. Every linear system with the same number of equations as unknowns has a unique solution. 1. For matrices A, B, C, A + B = A + C if and only if A = B. 2. Every linear system with the same number of equations as unknowns has a unique solution. 3. Every linear system with the same number of equations

More information

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

Lecture 6 & 7. Shuanglin Shao. September 16th and 18th, 2013 Lecture 6 & 7 Shuanglin Shao September 16th and 18th, 2013 1 Elementary matrices 2 Equivalence Theorem 3 A method of inverting matrices Def An n n matrice is called an elementary matrix if it can be obtained

More information

Linear Algebra: Lecture Notes. Dr Rachel Quinlan School of Mathematics, Statistics and Applied Mathematics NUI Galway

Linear Algebra: Lecture Notes. Dr Rachel Quinlan School of Mathematics, Statistics and Applied Mathematics NUI Galway Linear Algebra: Lecture Notes Dr Rachel Quinlan School of Mathematics, Statistics and Applied Mathematics NUI Galway November 6, 23 Contents Systems of Linear Equations 2 Introduction 2 2 Elementary Row

More information

MATRICES AND MATRIX OPERATIONS

MATRICES AND MATRIX OPERATIONS SIZE OF THE MATRIX is defined by number of rows and columns in the matrix. For the matrix that have m rows and n columns we say the size of the matrix is m x n. If matrix have the same number of rows (n)

More information

Linear Algebra 1 Exam 1 Solutions 6/12/3

Linear Algebra 1 Exam 1 Solutions 6/12/3 Linear Algebra 1 Exam 1 Solutions 6/12/3 Question 1 Consider the linear system in the variables (x, y, z, t, u), given by the following matrix, in echelon form: 1 2 1 3 1 2 0 1 1 3 1 4 0 0 0 1 2 3 Reduce

More information

Inverses and Determinants

Inverses and Determinants Engineering Mathematics 1 Fall 017 Inverses and Determinants I begin finding the inverse of a matrix; namely 1 4 The inverse, if it exists, will be of the form where AA 1 I; which works out to ( 1 4 A

More information

8 Matrices and operations on matrices

8 Matrices and operations on matrices AAC - Business Mathematics I Lecture #8, December 1, 007 Katarína Kálovcová 8 Matrices and operations on matrices Matrices: In mathematics, a matrix (plural matrices is a rectangular table of elements

More information

Determinants. 2.1 Determinants by Cofactor Expansion. Recall from Theorem that the 2 2 matrix

Determinants. 2.1 Determinants by Cofactor Expansion. Recall from Theorem that the 2 2 matrix CHAPTER 2 Determinants CHAPTER CONTENTS 21 Determinants by Cofactor Expansion 105 22 Evaluating Determinants by Row Reduction 113 23 Properties of Determinants; Cramer s Rule 118 INTRODUCTION In this chapter

More information

Elementary Row Operations on Matrices

Elementary Row Operations on Matrices King Saud University September 17, 018 Table of contents 1 Definition A real matrix is a rectangular array whose entries are real numbers. These numbers are organized on rows and columns. An m n matrix

More information

Review of Linear Algebra

Review of Linear Algebra Review of Linear Algebra Definitions An m n (read "m by n") matrix, is a rectangular array of entries, where m is the number of rows and n the number of columns. 2 Definitions (Con t) A is square if m=

More information

MTH 102A - Linear Algebra II Semester

MTH 102A - Linear Algebra II Semester MTH 0A - Linear Algebra - 05-6-II Semester Arbind Kumar Lal P Field A field F is a set from which we choose our coefficients and scalars Expected properties are ) a+b and a b should be defined in it )

More information

2 b 3 b 4. c c 2 c 3 c 4

2 b 3 b 4. c c 2 c 3 c 4 OHSx XM511 Linear Algebra: Multiple Choice Questions for Chapter 4 a a 2 a 3 a 4 b b 1. What is the determinant of 2 b 3 b 4 c c 2 c 3 c 4? d d 2 d 3 d 4 (a) abcd (b) abcd(a b)(b c)(c d)(d a) (c) abcd(a

More information

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

5x 2 = 10. x 1 + 7(2) = 4. x 1 3x 2 = 4. 3x 1 + 9x 2 = 8 1 To solve the system x 1 + x 2 = 4 2x 1 9x 2 = 2 we find an (easier to solve) equivalent system as follows: Replace equation 2 with (2 times equation 1 + equation 2): x 1 + x 2 = 4 Solve equation 2 for

More information

1 Determinants. 1.1 Determinant

1 Determinants. 1.1 Determinant 1 Determinants [SB], Chapter 9, p.188-196. [SB], Chapter 26, p.719-739. Bellow w ll study the central question: which additional conditions must satisfy a quadratic matrix A to be invertible, that is to

More information

Lecture 10: Determinants and Cramer s Rule

Lecture 10: Determinants and Cramer s Rule Lecture 0: Determinants and Cramer s Rule The determinant and its applications. Definition The determinant of a square matrix A, denoted by det(a) or A, is a real number, which is defined as follows. -by-

More information

Determinant of a Matrix

Determinant of a Matrix 13 March 2018 Goals We will define determinant of SQUARE matrices, inductively, using the definition of Minors and cofactors. We will see that determinant of triangular matrices is the product of its diagonal

More information

Methods for Solving Linear Systems Part 2

Methods for Solving Linear Systems Part 2 Methods for Solving Linear Systems Part 2 We have studied the properties of matrices and found out that there are more ways that we can solve Linear Systems. In Section 7.3, we learned that we can use

More information

Linear Algebra Practice Problems

Linear Algebra Practice Problems Math 7, Professor Ramras Linear Algebra Practice Problems () Consider the following system of linear equations in the variables x, y, and z, in which the constants a and b are real numbers. x y + z = a

More information

Equality: Two matrices A and B are equal, i.e., A = B if A and B have the same order and the entries of A and B are the same.

Equality: Two matrices A and B are equal, i.e., A = B if A and B have the same order and the entries of A and B are the same. Introduction Matrix Operations Matrix: An m n matrix A is an m-by-n array of scalars from a field (for example real numbers) of the form a a a n a a a n A a m a m a mn The order (or size) of A is m n (read

More information

Introduction to Matrices and Linear Systems Ch. 3

Introduction to Matrices and Linear Systems Ch. 3 Introduction to Matrices and Linear Systems Ch. 3 Doreen De Leon Department of Mathematics, California State University, Fresno June, 5 Basic Matrix Concepts and Operations Section 3.4. Basic Matrix Concepts

More information

William Stallings Copyright 2010

William Stallings Copyright 2010 A PPENDIX E B ASIC C ONCEPTS FROM L INEAR A LGEBRA William Stallings Copyright 2010 E.1 OPERATIONS ON VECTORS AND MATRICES...2 Arithmetic...2 Determinants...4 Inverse of a Matrix...5 E.2 LINEAR ALGEBRA

More information

Math 416, Spring 2010 The algebra of determinants March 16, 2010 THE ALGEBRA OF DETERMINANTS. 1. Determinants

Math 416, Spring 2010 The algebra of determinants March 16, 2010 THE ALGEBRA OF DETERMINANTS. 1. Determinants THE ALGEBRA OF DETERMINANTS 1. Determinants We have already defined the determinant of a 2 2 matrix: det = ad bc. We ve also seen that it s handy for determining when a matrix is invertible, and when it

More information

13. Systems of Linear Equations 1

13. Systems of Linear Equations 1 13. Systems of Linear Equations 1 Systems of linear equations One of the primary goals of a first course in linear algebra is to impress upon the student how powerful matrix methods are in solving systems

More information

MATH10212 Linear Algebra B Homework 7

MATH10212 Linear Algebra B Homework 7 MATH22 Linear Algebra B Homework 7 Students are strongly advised to acquire a copy of the Textbook: D C Lay, Linear Algebra and its Applications Pearson, 26 (or other editions) Normally, homework assignments

More information

spring, math 204 (mitchell) list of theorems 1 Linear Systems Linear Transformations Matrix Algebra

spring, math 204 (mitchell) list of theorems 1 Linear Systems Linear Transformations Matrix Algebra spring, 2016. math 204 (mitchell) list of theorems 1 Linear Systems THEOREM 1.0.1 (Theorem 1.1). Uniqueness of Reduced Row-Echelon Form THEOREM 1.0.2 (Theorem 1.2). Existence and Uniqueness Theorem THEOREM

More information

Vector Spaces and SubSpaces

Vector Spaces and SubSpaces Vector Spaces and SubSpaces Linear Algebra MATH 2076 Linear Algebra Vector Spaces & SubSpaces Chapter 4, Section 1b 1 / 10 What is a Vector Space? A vector space is a bunch of objects that we call vectors

More information

ANSWERS. E k E 2 E 1 A = B

ANSWERS. E k E 2 E 1 A = B MATH 7- Final Exam Spring ANSWERS Essay Questions points Define an Elementary Matrix Display the fundamental matrix multiply equation which summarizes a sequence of swap, combination and multiply operations,

More information

Math 317, Tathagata Basak, Some notes on determinant 1 Row operations in terms of matrix multiplication 11 Let I n denote the n n identity matrix Let E ij denote the n n matrix whose (i, j)-th entry is

More information

Lecture 12: Solving Systems of Linear Equations by Gaussian Elimination

Lecture 12: Solving Systems of Linear Equations by Gaussian Elimination Lecture 12: Solving Systems of Linear Equations by Gaussian Elimination Winfried Just, Ohio University September 22, 2017 Review: The coefficient matrix Consider a system of m linear equations in n variables.

More information