Announcements Wednesday, October 25

Size: px
Start display at page:

Download "Announcements Wednesday, October 25"

Transcription

1 Announcements Wednesday, October 25 The midterm will be returned in recitation on Friday. The grade breakdown is posted on Piazza. You can pick it up from me in office hours before then. Keep tabs on your grades on Canvas. No WeBWorK this week! No quiz on Friday! Withdraw deadline is this Saturday, 10/28. My office is Skiles 244. Rabinoffice hours are Monday, 1 3pm and Tuesday, 9 11am.

2 Orientation Last time: we learned the definition of the determinant.... to compute the determinant using row reduction.... all sorts of magical properties of the determinant, like det(ab) = det(a) det(b) the determinant computes volumes nonzero determinants characterize invertability etc. Today: we will learn... Special formulas for 2 2 and 3 3 matrices. How to compute determinants using cofactor expansions. How to compute inverses using determinants.

3 Determinants of 2 2 Matrices Reminder We already have a formula in the 2 2 case: a b det = ad bc. c d

4 Determinants of 3 3 Matrices Here s the formula: a 11 a 12 a 13 a11a22a33 + a12a23a31 + a13a21a32 det a 21 a 22 a 23 = a 31 a 32 a a 33 13a 22a 31 a 11a 23a 32 a 12a 21a 33 How on earth do you remember this? Draw a bigger matrix, repeating the first two columns to the right: a 11 a 12 a 13 a 11 a 12 + a 21 a 22 a 23 a 21 a 22 a 31 a 32 a 33 a 31 a 32 a 11 a 12 a 13 a 11 a 12 a 21 a 22 a 23 a 21 a 22 a 31 a 32 a 33 a 31 a 32 Then add the products of the downward diagonals, and subtract the product of the upward diagonals. For example, det = = =

5 Cofactor Expansions When n 4, the determinant isn t just a sum of products of diagonals. The formula is recursive: you compute a larger determinant in terms of smaller ones. First some notation. Let A be an n n matrix. A ij = ijth minor of A = (n 1) (n 1) matrix you get by deleting the ith row and jth column C ij = ( 1) i+j det A ij = ijth cofactor of A The signs of the cofactors follow a checkerboard pattern: ± in the ij entry is the sign of C ij + + Theorem The determinant of an n n matrix A is n det(a) = a 1j C 1j = a 11C 11 + a 12C a 1nC 1n. j=1 This formula is called cofactor expansion along the first row.

6 Cofactor Expansions 1 1 Matrices This is the beginning of the recursion. det( a 11 ) = a 11.

7 Cofactor Expansions 2 2 Matrices a11 a 12 A = a 21 a 22 The minors are: a11 a 12 A 11 = = ( a a 21 a 22 ) A 12 = 22 a11 a 12 A 21 = = ( a a 21 a 12 ) A 22 = 22 a11 a 12 = ( a a 21 a 21 ) 22 a11 a 12 = ( a a 21 a 11 ) 22 The cofactors are C 11 = + det A 11 = a 22 C 12 = det A 12 = a 21 C 21 = det A 21 = a 12 C 22 = + det A 22 = a 11 The determinant is det A = a 11C 11 + a 12C 12 = a 11a 22 a 12a 21.

8 Cofactor Expansions 3 3 Matrices a 11 a 12 a 13 A = a 21 a 22 a 23 a 31 a 32 a 33 The top row minors and cofactors are: a 11 a 12 a 13 A 11 = a 21 a 22 a 23 a22 a 23 = a a 31 a 32 a 32 a a 11 a 12 a 13 A 12 = a 21 a 22 a 23 a21 a 23 = a a 31 a 32 a 31 a a 11 a 12 a 13 A 13 = a 21 a 22 a 23 a21 a 22 = a a 31 a 32 a 31 a The determinant is magically the same formula as before: det A = a 11C 11 + a 12C 12 + a 13C 13 ( a22 a 23 a21 a 23 = a 11 det a a 32 a 12 det 33 a 31 a 33 a22 a 23 C 11 = + det a 32 a 33 a21 a 23 C 12 = det a 31 a 33 a21 a 22 C 13 = + det a 31 a 32 ) + a 13 det a21 a 22 a 31 a 32

9 Cofactor Expansions Example det = 5 det det det ( = 5 det 1 det = 5 ( 3 0) 1 (1 8) = = ) + 0 det

10 2n 1 More Formulas for the Determinant Recall: the formula det(a) = n a 1j C 1j = a 11C 11 + a 12C a 1nC 1n. j=1 is called cofactor expansion along the first row. Actually, you can expand cofactors along any row or column you like! Magical Theorem The determinant of an n n matrix A is n det A = a ij C ij for any fixed i det A = j=1 n a ij C ij i=1 for any fixed j These formulas are called cofactor expansion along the ith row, respectively, jth column. In particular, you get the same answer whichever row or column you choose. Try this with a row or a column with a lot of zeros.

11 Cofactor Expansion Example A = It looks easiest to expand along the third column: don t don t det A = 0 det 0 det + 1 det care care = det = 2 1 = 1 1 1

12 Cofactor Expansion Advice In general, computing a determinant by cofactor expansion is slower than by row reduction. It makes sense to expand by cofactors if you have a row or column with a lot of zeros. Also if your matrix has unknowns in it, since those are hard to row reduce (you don t know where the pivots are). You can also use more than one method; for example: Use cofactors on a 4 4 matrix but compute the minors using the 3 3 formula. Do row operations to produce a row/column with lots of zeros, then expand cofactors (but keep track of how you changed the determinant!). Example: det R 2=R 2 +2R ======== 3 det rd column 5 1 ======= ( 1) det = 8 7 3

13 Poll Poll det =? A. 84 B. 28 C. 7 D. 0 E. 7 F. 28 G. 84 Repeatedly expanding along the first row, you get: det = 1 det = ( 1) 7 det = ( 1) 7 3 det = ( 1) = 84.

14 A Formula for the Inverse For fun from 3.3 For 2 2 matrices we had a nice formula for the inverse: a b A = = A 1 1 d b = = 1 ( C11 C 21 c d ad bc c a det A C 12 C 22 ). Theorem This last formula works for any n n invertible matrix A: (3, 1) entry C 11 C 21 C 31 C n1 A 1 = 1 C 12 C 22 C 32 C n2 C 13 C 23 C 33 C n3 = 1 T Cij det A det A C 1n C 2n C 3n C nn Note that the cofactors are transposed : the (i, j) entry of the matrix is C ji. The proof uses Cramer s rule.

15 A Formula for the Inverse Example Compute A 1, where A = The minors are: A 11 = A = A 21 = A = A 31 = A = A 13 = A 23 = A 33 = 0 1 The cofactors are (don t forget to multiply by ( 1) i+j ): C 11 = 1 C 12 = 1 C 13 = 1 C 21 = 1 C 22 = 1 C 23 = 1 C 31 = 1 C 32 = 1 C 33 = 1 The determinant is (expanding along the first row): det A = 1 C C C 13 = 2

16 A Formula for the Inverse Example, continued Compute A 1, where A = The inverse is A 1 = 1 C 11 C 21 C 31 C 12 C 22 C 32 = det A 2 C 13 C 23 C Check: = "

17 A Formula for the Inverse Why? A 1 = 1 det A C 11 C 21 C 31 C n1 C 12 C 22 C 32 C n2 C 13 C 23 C 33 C n C 1n C 2n C 3n C nn That was a lot of work! It s way easier to compute inverses by row reduction. The formula is good for error estimates: the only division is by the determinant, so if your determinant is tiny, your error bars are large. It s also useful if your matrix has unknowns in it. It s part of a larger picture in the theory.

18 Summary We have several ways to compute the determinant of a matrix. Special formulas for 2 2 and 3 3 matrices. These work great for small matrices. Cofactor expansion. This is perfect when there is a row or column with a lot of zeros, or if your matrix has unknowns in it. Row reduction. This is the way to go when you have a big matrix which doesn t have a row or column with a lot of zeros. Any combination of the above. Cofactor expansion is recursive, but you don t have to use cofactor expansion to compute the determinants of the minors! Or you can do row operations and then a cofactor expansion.

Announcements Wednesday, October 04

Announcements Wednesday, October 04 Announcements Wednesday, October 04 Please fill out the mid-semester survey under Quizzes on Canvas. WeBWorK 1.8, 1.9 are due today at 11:59pm. The quiz on Friday covers 1.7, 1.8, and 1.9. My office is

More information

Announcements Wednesday, September 27

Announcements Wednesday, September 27 Announcements Wednesday, September 27 The midterm will be returned in recitation on Friday. You can pick it up from me in office hours before then. Keep tabs on your grades on Canvas. WeBWorK 1.7 is due

More information

Announcements Monday, October 02

Announcements Monday, October 02 Announcements Monday, October 02 Please fill out the mid-semester survey under Quizzes on Canvas WeBWorK 18, 19 are due Wednesday at 11:59pm The quiz on Friday covers 17, 18, and 19 My office is Skiles

More information

Announcements Wednesday, November 7

Announcements Wednesday, November 7 Announcements Wednesday, November 7 The third midterm is on Friday, November 6 That is one week from this Friday The exam covers 45, 5, 52 53, 6, 62, 64, 65 (through today s material) WeBWorK 6, 62 are

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

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

Announcements Monday, September 18

Announcements Monday, September 18 Announcements Monday, September 18 WeBWorK 1.4, 1.5 are due on Wednesday at 11:59pm. The first midterm is on this Friday, September 22. Midterms happen during recitation. The exam covers through 1.5. About

More information

Announcements Wednesday, November 7

Announcements Wednesday, November 7 Announcements Wednesday, November 7 The third midterm is on Friday, November 16 That is one week from this Friday The exam covers 45, 51, 52 53, 61, 62, 64, 65 (through today s material) WeBWorK 61, 62

More information

Announcements Wednesday, October 10

Announcements Wednesday, October 10 Announcements Wednesday, October 10 The second midterm is on Friday, October 19 That is one week from this Friday The exam covers 35, 36, 37, 39, 41, 42, 43, 44 (through today s material) WeBWorK 42, 43

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

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

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

Announcements Wednesday, August 30

Announcements Wednesday, August 30 Announcements Wednesday, August 30 WeBWorK due on Friday at 11:59pm. The first quiz is on Friday, during recitation. It covers through Monday s material. Quizzes mostly test your understanding of the homework.

More information

Announcements Wednesday, November 01

Announcements Wednesday, November 01 Announcements Wednesday, November 01 WeBWorK 3.1, 3.2 are due today at 11:59pm. The quiz on Friday covers 3.1, 3.2. My office is Skiles 244. Rabinoffice hours are Monday, 1 3pm and Tuesday, 9 11am. Section

More information

Announcements Monday, September 25

Announcements Monday, September 25 Announcements Monday, September 25 The midterm will be returned in recitation on Friday. You can pick it up from me in office hours before then. Keep tabs on your grades on Canvas. WeBWorK 1.7 is due Friday

More information

Announcements Wednesday, August 30

Announcements Wednesday, August 30 Announcements Wednesday, August 30 WeBWorK due on Friday at 11:59pm. The first quiz is on Friday, during recitation. It covers through Monday s material. Quizzes mostly test your understanding of the homework.

More information

Announcements Wednesday, November 01

Announcements Wednesday, November 01 Announcements Wednesday, November 01 WeBWorK 3.1, 3.2 are due today at 11:59pm. The quiz on Friday covers 3.1, 3.2. My office is Skiles 244. Rabinoffice hours are Monday, 1 3pm and Tuesday, 9 11am. Section

More information

Topic 15 Notes Jeremy Orloff

Topic 15 Notes Jeremy Orloff Topic 5 Notes Jeremy Orloff 5 Transpose, Inverse, Determinant 5. Goals. Know the definition and be able to compute the inverse of any square matrix using row operations. 2. Know the properties of inverses.

More information

Announcements Wednesday, September 20

Announcements Wednesday, September 20 Announcements Wednesday, September 20 WeBWorK 1.4, 1.5 are due on Wednesday at 11:59pm. The first midterm is on this Friday, September 22. Midterms happen during recitation. The exam covers through 1.5.

More information

Math 320, spring 2011 before the first midterm

Math 320, spring 2011 before the first midterm Math 320, spring 2011 before the first midterm Typical Exam Problems 1 Consider the linear system of equations 2x 1 + 3x 2 2x 3 + x 4 = y 1 x 1 + 3x 2 2x 3 + 2x 4 = y 2 x 1 + 2x 3 x 4 = y 3 where x 1,,

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

Determinants of 2 2 Matrices

Determinants of 2 2 Matrices Determinants In section 4, we discussed inverses of matrices, and in particular asked an important question: How can we tell whether or not a particular square matrix A has an inverse? We will be able

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

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

22A-2 SUMMER 2014 LECTURE 5

22A-2 SUMMER 2014 LECTURE 5 A- SUMMER 0 LECTURE 5 NATHANIEL GALLUP Agenda Elimination to the identity matrix Inverse matrices LU factorization Elimination to the identity matrix Previously, we have used elimination to get a system

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

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

Announcements Monday, September 17

Announcements Monday, September 17 Announcements Monday, September 17 WeBWorK 3.3, 3.4 are due on Wednesday at 11:59pm. The first midterm is on this Friday, September 21. Midterms happen during recitation. The exam covers through 3.4. About

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

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

1 Last time: determinants

1 Last time: determinants 1 Last time: determinants Let n be a positive integer If A is an n n matrix, then its determinant is the number det A = Π(X, A)( 1) inv(x) X S n where S n is the set of n n permutation matrices Π(X, A)

More information

Announcements Monday, October 29

Announcements Monday, October 29 Announcements Monday, October 29 WeBWorK on determinents due on Wednesday at :59pm. The quiz on Friday covers 5., 5.2, 5.3. My office is Skiles 244 and Rabinoffice hours are: Mondays, 2 pm; Wednesdays,

More information

Announcements Wednesday, September 05

Announcements Wednesday, September 05 Announcements Wednesday, September 05 WeBWorK 2.2, 2.3 due today at 11:59pm. The quiz on Friday coers through 2.3 (last week s material). My office is Skiles 244 and Rabinoffice hours are: Mondays, 12

More information

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

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

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

Math 4A Notes. Written by Victoria Kala Last updated June 11, 2017 Math 4A Notes Written by Victoria Kala vtkala@math.ucsb.edu Last updated June 11, 2017 Systems of Linear Equations A linear equation is an equation that can be written in the form a 1 x 1 + a 2 x 2 +...

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

Lecture 8: Determinants I

Lecture 8: Determinants I 8-1 MATH 1B03/1ZC3 Winter 2019 Lecture 8: Determinants I Instructor: Dr Rushworth January 29th Determinants via cofactor expansion (from Chapter 2.1 of Anton-Rorres) Matrices encode information. Often

More information

Math 250B Midterm I Information Fall 2018

Math 250B Midterm I Information Fall 2018 Math 250B Midterm I Information Fall 2018 WHEN: Wednesday, September 26, in class (no notes, books, calculators I will supply a table of integrals) EXTRA OFFICE HOURS: Sunday, September 23 from 8:00 PM

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

Announcements Monday, November 13

Announcements Monday, November 13 Announcements Monday, November 13 The third midterm is on this Friday, November 17 The exam covers 31, 32, 51, 52, 53, and 55 About half the problems will be conceptual, and the other half computational

More information

c c c c c c c c c c a 3x3 matrix C= has a determinant determined by

c c c c c c c c c c a 3x3 matrix C= has a determinant determined by Linear Algebra Determinants and Eigenvalues Introduction: Many important geometric and algebraic properties of square matrices are associated with a single real number revealed by what s known as the determinant.

More information

Math 103, Summer 2006 Determinants July 25, 2006 DETERMINANTS. 1. Some Motivation

Math 103, Summer 2006 Determinants July 25, 2006 DETERMINANTS. 1. Some Motivation DETERMINANTS 1. Some Motivation Today we re going to be talking about erminants. We ll see the definition in a minute, but before we get into ails I just want to give you an idea of why we care about erminants.

More information

Math Lecture 26 : The Properties of Determinants

Math Lecture 26 : The Properties of Determinants Math 2270 - Lecture 26 : The Properties of Determinants Dylan Zwick Fall 202 The lecture covers section 5. from the textbook. The determinant of a square matrix is a number that tells you quite a bit about

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

ENGR-1100 Introduction to Engineering Analysis. Lecture 21. Lecture outline

ENGR-1100 Introduction to Engineering Analysis. Lecture 21. Lecture outline ENGR-1100 Introduction to Engineering Analysis Lecture 21 Lecture outline Procedure (algorithm) for finding the inverse of invertible matrix. Investigate the system of linear equation and invertibility

More information

Announcements Monday, November 13

Announcements Monday, November 13 Announcements Monday, November 13 The third midterm is on this Friday, November 17. The exam covers 3.1, 3.2, 5.1, 5.2, 5.3, and 5.5. About half the problems will be conceptual, and the other half computational.

More information

Math 520 Exam 2 Topic Outline Sections 1 3 (Xiao/Dumas/Liaw) Spring 2008

Math 520 Exam 2 Topic Outline Sections 1 3 (Xiao/Dumas/Liaw) Spring 2008 Math 520 Exam 2 Topic Outline Sections 1 3 (Xiao/Dumas/Liaw) Spring 2008 Exam 2 will be held on Tuesday, April 8, 7-8pm in 117 MacMillan What will be covered The exam will cover material from the lectures

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

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

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

ENGR-1100 Introduction to Engineering Analysis. Lecture 21

ENGR-1100 Introduction to Engineering Analysis. Lecture 21 ENGR-1100 Introduction to Engineering Analysis Lecture 21 Lecture outline Procedure (algorithm) for finding the inverse of invertible matrix. Investigate the system of linear equation and invertibility

More information

Cofactors and Laplace s expansion theorem

Cofactors and Laplace s expansion theorem Roberto s Notes on Linear Algebra Chapter 5: Determinants Section 3 Cofactors and Laplace s expansion theorem What you need to know already: What a determinant is. How to use Gauss-Jordan elimination to

More information

Introduction to Determinants

Introduction to Determinants Introduction to Determinants For any square matrix of order 2, we have found a necessary and sufficient condition for invertibility. Indeed, consider the matrix The matrix A is invertible if and only if.

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

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

if we factor non-zero factors out of rows, we factor the same factors out of the determinants.

if we factor non-zero factors out of rows, we factor the same factors out of the determinants. Theorem: Let A n n. Then A 1 exists if and only if det A 0. proof: We already know that A 1 exists if and only if the reduced row echelon form of A is the identity matrix. Now, consider reducing A to its

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

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

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

Gaussian Elimination and Back Substitution

Gaussian Elimination and Back Substitution Jim Lambers MAT 610 Summer Session 2009-10 Lecture 4 Notes These notes correspond to Sections 31 and 32 in the text Gaussian Elimination and Back Substitution The basic idea behind methods for solving

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

Announcements Monday, November 26

Announcements Monday, November 26 Announcements Monday, November 26 Please fill out your CIOS survey! WeBWorK 6.6, 7.1, 7.2 are due on Wednesday. No quiz on Friday! But this is the only recitation on chapter 7. My office is Skiles 244

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

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

Determinants: summary of main results

Determinants: summary of main results Determinants: summary of main results A determinant of an n n matrix is a real number associated with this matrix. Its definition is complex for the general case We start with n = 2 and list important

More information

Linear Algebra Section 2.6 : LU Decomposition Section 2.7 : Permutations and transposes Wednesday, February 13th Math 301 Week #4

Linear Algebra Section 2.6 : LU Decomposition Section 2.7 : Permutations and transposes Wednesday, February 13th Math 301 Week #4 Linear Algebra Section. : LU Decomposition Section. : Permutations and transposes Wednesday, February 1th Math 01 Week # 1 The LU Decomposition We learned last time that we can factor a invertible matrix

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

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

Evaluating Determinants by Row Reduction

Evaluating Determinants by Row Reduction Evaluating Determinants by Row Reduction MATH 322, Linear Algebra I J. Robert Buchanan Department of Mathematics Spring 2015 Objectives Reduce a matrix to row echelon form and evaluate its determinant.

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

Math 215 HW #9 Solutions

Math 215 HW #9 Solutions Math 5 HW #9 Solutions. Problem 4.4.. If A is a 5 by 5 matrix with all a ij, then det A. Volumes or the big formula or pivots should give some upper bound on the determinant. Answer: Let v i be the ith

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

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

Math 110 Linear Algebra Midterm 2 Review October 28, 2017

Math 110 Linear Algebra Midterm 2 Review October 28, 2017 Math 11 Linear Algebra Midterm Review October 8, 17 Material Material covered on the midterm includes: All lectures from Thursday, Sept. 1st to Tuesday, Oct. 4th Homeworks 9 to 17 Quizzes 5 to 9 Sections

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

Determinants in detail

Determinants in detail Determinants in detail Kyle Miller September 27, 2016 The book s introduction to the determinant det A of an n n square matrix A is to say there is a quantity which determines exactly when A is invertible,

More information

TOPIC III LINEAR ALGEBRA

TOPIC III LINEAR ALGEBRA [1] Linear Equations TOPIC III LINEAR ALGEBRA (1) Case of Two Endogenous Variables 1) Linear vs. Nonlinear Equations Linear equation: ax + by = c, where a, b and c are constants. 2 Nonlinear equation:

More information

Notes on Determinants and Matrix Inverse

Notes on Determinants and Matrix Inverse Notes on Determinants and Matrix Inverse University of British Columbia, Vancouver Yue-Xian Li March 17, 2015 1 1 Definition of determinant Determinant is a scalar that measures the magnitude or size of

More information

1 Matrices and Systems of Linear Equations. a 1n a 2n

1 Matrices and Systems of Linear Equations. a 1n a 2n March 31, 2013 16-1 16. Systems of Linear Equations 1 Matrices and Systems of Linear Equations An m n matrix is an array A = (a ij ) of the form a 11 a 21 a m1 a 1n a 2n... a mn where each a ij is a real

More information

1111: Linear Algebra I

1111: Linear Algebra I 1111: Linear Algebra I Dr. Vladimir Dotsenko (Vlad) Michaelmas Term 2015 Dr. Vladimir Dotsenko (Vlad) 1111: Linear Algebra I Michaelmas Term 2015 1 / 10 Row expansion of the determinant Our next goal is

More information

Digital Workbook for GRA 6035 Mathematics

Digital Workbook for GRA 6035 Mathematics Eivind Eriksen Digital Workbook for GRA 6035 Mathematics November 10, 2014 BI Norwegian Business School Contents Part I Lectures in GRA6035 Mathematics 1 Linear Systems and Gaussian Elimination........................

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

[Disclaimer: This is not a complete list of everything you need to know, just some of the topics that gave people difficulty.]

[Disclaimer: This is not a complete list of everything you need to know, just some of the topics that gave people difficulty.] Math 43 Review Notes [Disclaimer: This is not a complete list of everything you need to know, just some of the topics that gave people difficulty Dot Product If v (v, v, v 3 and w (w, w, w 3, then the

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

M. Matrices and Linear Algebra

M. Matrices and Linear Algebra M. Matrices and Linear Algebra. Matrix algebra. In section D we calculated the determinants of square arrays of numbers. Such arrays are important in mathematics and its applications; they are called matrices.

More information

Math 18.6, Spring 213 Problem Set #6 April 5, 213 Problem 1 ( 5.2, 4). Identify all the nonzero terms in the big formula for the determinants of the following matrices: 1 1 1 2 A = 1 1 1 1 1 1, B = 3 4

More information

Diagonalization. MATH 1502 Calculus II Notes. November 4, 2008

Diagonalization. MATH 1502 Calculus II Notes. November 4, 2008 Diagonalization MATH 1502 Calculus II Notes November 4, 2008 We want to understand all linear transformations L : R n R m. The basic case is the one in which n = m. That is to say, the case in which the

More information

MATRIX DETERMINANTS. 1 Reminder Definition and components of a matrix

MATRIX DETERMINANTS. 1 Reminder Definition and components of a matrix MATRIX DETERMINANTS Summary Uses... 1 1 Reminder Definition and components of a matrix... 1 2 The matrix determinant... 2 3 Calculation of the determinant for a matrix... 2 4 Exercise... 3 5 Definition

More information

IMPORTANT DEFINITIONS AND THEOREMS REFERENCE SHEET

IMPORTANT DEFINITIONS AND THEOREMS REFERENCE SHEET IMPORTANT DEFINITIONS AND THEOREMS REFERENCE SHEET This is a (not quite comprehensive) list of definitions and theorems given in Math 1553. Pay particular attention to the ones in red. Study Tip For each

More information

Announcements Wednesday, November 15

Announcements Wednesday, November 15 Announcements Wednesday, November 15 The third midterm is on this Friday, November 17. The exam covers 3.1, 3.2, 5.1, 5.2, 5.3, and 5.5. About half the problems will be conceptual, and the other half computational.

More information

Things we can already do with matrices. Unit II - Matrix arithmetic. Defining the matrix product. Things that fail in matrix arithmetic

Things we can already do with matrices. Unit II - Matrix arithmetic. Defining the matrix product. Things that fail in matrix arithmetic Unit II - Matrix arithmetic matrix multiplication matrix inverses elementary matrices finding the inverse of a matrix determinants Unit II - Matrix arithmetic 1 Things we can already do with matrices equality

More information

Announcements Monday, November 26

Announcements Monday, November 26 Announcements Monday, November 26 Please fill out your CIOS survey! WeBWorK 6.6, 7.1, 7.2 are due on Wednesday. No quiz on Friday! But this is the only recitation on chapter 7. My office is Skiles 244

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

MAC Learning Objectives. Learning Objectives (Cont.) Module 10 System of Equations and Inequalities II

MAC Learning Objectives. Learning Objectives (Cont.) Module 10 System of Equations and Inequalities II MAC 1140 Module 10 System of Equations and Inequalities II Learning Objectives Upon completing this module, you should be able to 1. represent systems of linear equations with matrices. 2. transform a

More information

MTH 464: Computational Linear Algebra

MTH 464: Computational Linear Algebra MTH 464: Computational Linear Algebra Lecture Outlines Exam 2 Material Prof. M. Beauregard Department of Mathematics & Statistics Stephen F. Austin State University March 2, 2018 Linear Algebra (MTH 464)

More information

Introduction to Matrices

Introduction to Matrices 214 Analysis and Design of Feedback Control Systems Introduction to Matrices Derek Rowell October 2002 Modern system dynamics is based upon a matrix representation of the dynamic equations governing the

More information

Math Bootcamp An p-dimensional vector is p numbers put together. Written as. x 1 x =. x p

Math Bootcamp An p-dimensional vector is p numbers put together. Written as. x 1 x =. x p Math Bootcamp 2012 1 Review of matrix algebra 1.1 Vectors and rules of operations An p-dimensional vector is p numbers put together. Written as x 1 x =. x p. When p = 1, this represents a point in the

More information

This MUST hold matrix multiplication satisfies the distributive property.

This MUST hold matrix multiplication satisfies the distributive property. The columns of AB are combinations of the columns of A. The reason is that each column of AB equals A times the corresponding column of B. But that is a linear combination of the columns of A with coefficients

More information