Lecture 2 Mathcad basics and Matrix Operations

Size: px
Start display at page:

Download "Lecture 2 Mathcad basics and Matrix Operations"

Transcription

1 Lecture 2 Mathcad basics and Matrix Operations Announcements No class or lab Wednesday, 8/29/01 I will be posting a lab worksheet on the web site on Tuesday for you to work through on your own. Operators + Addition, - Subtraction, * Multiplication, / Division, ^ Power ( ) Specify evaluation order Order of Operations ( ) ^ highest level, first priority * / next priority level + - last operations to be performed y := 2 x := 3 * y^2 x = 12 y := 2 x := (3*y)^2 x = 36 y := 2 x := 3 * y + 2 x = 8 z := 3*6+6*2/4 z = 21 x := 5^2/2 x = 12.5 Matrix operations: Mathcad is designed to be a tool for quick and easy manipulation of matrix forms of data. We ve seen the matrix before in Lecture 1 as a 2-D array. That is, many pieces of information are stored under a single name. Different pieces of information are then retrieved by pointing to different parts of the matrix by row and column. Here we will learn some basic matrix operations: Adding and Subtracting, Transpose, Multiplication. Adding matrices Add two matrices together is just the addition of each of their respective elements. If A and B are both matrices of the same dimensions (size), then Lecture 2 Mathcad basics and Matrix Operations page 11 of 18

2 C := A + B produces C, where the i th row and j th column are just the addition of the elements (numbers) in the i th row and j th column of A and B Given:!!" #, and " ' ( ) $%!! *!+!' so that the addition is : #,-!. " " $!!!#!% '" The Mathcad commands to perform these matrix assignments and the addition are: A := Ctrl-M (choose 2 x 3) B := Ctrl-M (choose 2 x 3) C := A + B C = Rule: A, B, and C must all have the same dimensions Transpose Transposing a matrix means swapping rows and columns of a matrix. No matrix dimension restrictions Some examples: 1-D! #'%,! $ # ' 1x3 becomes ==> 3x1 % 2-D " */! 0 (/# 0 $/), " $ */! "/' 0 (/# "/! 2x3 becomes ==> 3x2 "/' "/! "/% 0 $/) "/% In general "% (, ) " $ (, %) In Mathcad, The transpose is can be keystroked by Ctrl - 1 (the number one) " #")' %*($ B Ctrl-1 = '() #% "* )( '$ Lecture 2 Mathcad basics and Matrix Operations page 12 of 18

3 Multiplication Multiplication of matrices is not as simple as addition or subtraction. It is not an element by element multiplication as you might suspect it would be. Rather, matrix multiplication is the result of the dot products of rows in one matrix with columns of another. Consider: C := A * B matrix multiplication gives the i th row and k th column spot in C as the scalar results of the dot product of the i th row in A with the k th column in B. In equation form this looks like: 2,34,536789:,;9,< # %, *! %,,1,", *! Let s break this down in a step-by-step example: Step 1: Dot Product (a 1-row matrix times a 1-column matrix) The Dot product is the scalar result of multiplying one row by one column ) '#" 1 * '1).#1*."1$ $" DOT PRODUCT OF ROW AND COLUMN 1x1 1x3 $ 3x1 Rule: 1) # of elements in the row and column must be the same 2) must be a row times a column, not a column times a row Step 2: general matrix multiplication is taking a series of dot products each row in pre-matrix by each column in post-matrix # )!(' 1 *!'!1#.(1*.'1!+,,,,!1).(1!'.'1!! #$ $) %"$ %1#."1*.$1!+,,,,%1)."1!'.$1!!!"%!)$!+!! 2x3 3x2 2x2 C(i,k) is the result of the dot product of row i in A with column k in B Matrix Multiplication Rules: 1) The # of columns in the pre-matrix must equal # of rows in post-matrix inner matrix dimensions must agree 2) The result of the multiplication will have the outer dimensions # rows in pre-matrix by # columns in post-matrix Lecture 2 Mathcad basics and Matrix Operations page 13 of 18

4 For this example, apply rules C := A * B A is nra x nca (# rows in a by # columns in a) B is nrb x ncb Rule 1 says: nca = nrb or else we can t multiply (can t take dot products with different number of terms in row and column) Rule 2 says: C will be of size nra x ncb result C has outer dimensions (+',,,(-',1,(+.,,,(-. inner dimensions must agree How to perform matrix multiplication in Mathcad??? Easy A := [4 5; 2 1] B := [9 1; 6 12] C := A*B Note: Now that we know how to enter a matrix into Mathcad, I ll use a shortcut notation for these notes as applied above, where: A := [4 5; 2 1] means a 2 x 2 array where the ; indicates the start of the next row. The ; is not actually used in Mathcad for this purpose, its just a shorthand notation that I ll use for these notes. D := [ ; ] is a 2 x 3 matrix using this notation Note: If inner matrix dimensions don t match, Mathcad can t perform the operation since it violates the rules of matrix multiplication, and you ll get an error that says: the number of rows and or columns in these arrays do not match Lecture 2 Mathcad basics and Matrix Operations page 14 of 18

5 example: Let s try to multiply a 2x3 by another 2x3 (rules say we can t do this) A := [3 4 1 ; 0 4 9]; B := [2 9 5 ; 9 4 5]; C := A * B Mathcad will tell you: the number of rows and or columns in these arrays do not match and won t provide an answer Since the # of columns in A was not equal to # of rows in B, we can t multiply A * B IMPORTANT: Another example: Say we create a 1-D vector x with the following: x := [ ]; Now say we want to square each number in x. It would seem natural to do this: y := x^2 But Mathcad tells us: This Matrix must be square. It should have the same number of rows as columns Note that y : = x^2 is the same as saying y := x*x Mathcad by default will always interpret any multiplication as a standard dot product type matrix multiplication, thus we can t take a dot product of two row vectors, since rules of matrix multiplication are violated in this case. The exception to this default assumption in Mathcad is if the vector is a column instead of a row. In that case, Mathcad will assume you want to square each element in the vector rather that apply standard matrix multiplication. If we just want to square the numbers in x, we can do this: y = x Ctrl-1 shift ^2 This first transposes the row vector into a column vector, then squares the elements in the vector Try this out a:= ( 2 5 4) ( ) 2 4 a T = Lecture 2 Mathcad basics and Matrix Operations page 15 of 18

6 Practice matrix operations on the following examples. List the size of the resulting matrix first. then perform the operations by hands. Use Mathcad to confirm each of your answers. %!'# 1 ' * " %$ ") $! ' ( ) *!+!' ( % $ 1 '!* (" '! 1 *$ %) (%* $ 1 '$!!(% *)( 1 "+ %" ($ ($ #" $. 1!+ ' $ *% +! ) " # We will consider the use of matrices to solve a number of different problems in the numerical methods portion of the course. Lecture 2 Mathcad basics and Matrix Operations page 16 of 18

7 Fundamental Program Structure Labeling the program using comments program title student information program summary executable statements program input (load data from external files, assignment statements, etc.) perform operations needed (sequential execution, loops, etc.) display program output (graphs, numbers, output files, etc.) intersperse comments to explain program Example program #1 K., CGN 3421, August 27, 2001 This program demonstrates basic program structure INPUT SECTION x:= CALCULATION SECTION ( ) 2 y := x + x CREATE scalar y as a function 1 4 of x1 and x4 40 z:= x 2 + y 261 CREATE z vector from x and y z = 100 NOTE that x^2 operates on each value in x 52 OUTPUT SECTION 300 z x graph of z vs. x NOTE that the plot plots the x values in order of appearance it does not reorder and sort Lecture 2 Mathcad basics and Matrix Operations page 17 of 18

8 Vector operations Note in the previous example that z was created from the vector x and the scalar y. Mathcad knew how to handle the combination based on its default assumptions, and the resultant variable z is a vector. This is an example of a vector operation. That is, we did not have to write an algorithm to explicitly calculate each of the values in z one at a time. However, we will see later that it is important to know how to operate on one element at a time within a vector or matrix. In the previous example, we could have used a for loop to explicitly calculate each element of z, one at a time. Simply replace the Calculation section with the following CALCULATION SECTION ( ) 2 y := x + 1 x CREATE scalar y as a function 4 of x1 and x4 z := for i zz zz i 1.. length() x ( x i ) 2 + y z = CREATE z vector from x and y Another example of vector operation Plot the following function over the range / '. ", 0 ', '. +/', ", 0 #!+ yx ():= 2+ 3x 2x x 3 CREATE FUNCTION x:= 5, CREATE Range Vector 50 yx ( ) 0 50 PLOT of function x Lecture 2 Mathcad basics and Matrix Operations page 18 of 18

Lecture 2 Mathcad Basics

Lecture 2 Mathcad Basics Operators Lecture 2 Mathcad Basics + Addition, - Subtraction, * Multiplication, / Division, ^ Power ( ) Specify evaluation order Order of Operations ( ) ^ highest level, first priority * / next priority

More information

CGN 3421 - Computer Methods

CGN 3421 - Computer Methods CGN 3421 - Computer Methods Class web site: www.ce.ufl.edu/~kgurl Class text books: Recommended as a reference Numerical Methods for Engineers, Chapra and Canale Fourth Edition, McGraw-Hill Class software:

More information

AMATH 352 Lecture 3 MATLAB Tutorial Starting MATLAB Entering Variables

AMATH 352 Lecture 3 MATLAB Tutorial Starting MATLAB Entering Variables AMATH 352 Lecture 3 MATLAB Tutorial MATLAB (short for MATrix LABoratory) is a very useful piece of software for numerical analysis. It provides an environment for computation and the visualization. Learning

More information

Chapter 19. General Matrices. An n m matrix is an array. a 11 a 12 a 1m a 21 a 22 a 2m A = a n1 a n2 a nm. The matrix A has n row vectors

Chapter 19. General Matrices. An n m matrix is an array. a 11 a 12 a 1m a 21 a 22 a 2m A = a n1 a n2 a nm. The matrix A has n row vectors Chapter 9. General Matrices An n m matrix is an array a a a m a a a m... = [a ij]. a n a n a nm The matrix A has n row vectors and m column vectors row i (A) = [a i, a i,..., a im ] R m a j a j a nj col

More information

PTC Mathcad Prime 3.0 Keyboard Shortcuts

PTC Mathcad Prime 3.0 Keyboard Shortcuts PTC Mathcad Prime 3.0 Shortcuts Swedish s Regions Inserting Regions Operator/Command Description Shortcut Swedish Area Inserts a collapsible area you can collapse or expand to toggle the display of your

More information

Matrix Multiplication

Matrix Multiplication Matrix Multiplication CPS343 Parallel and High Performance Computing Spring 2016 CPS343 (Parallel and HPC) Matrix Multiplication Spring 2016 1 / 32 Outline 1 Matrix operations Importance Dense and sparse

More information

3.2 Matrix Multiplication

3.2 Matrix Multiplication 3.2 Matrix Multiplication Question : How do you multiply two matrices? Question 2: How do you interpret the entries in a product of two matrices? When you add or subtract two matrices, you add or subtract

More information

Typical Linear Equation Set and Corresponding Matrices

Typical Linear Equation Set and Corresponding Matrices EWE: Engineering With Excel Larsen Page 1 4. Matrix Operations in Excel. Matrix Manipulations: Vectors, Matrices, and Arrays. How Excel Handles Matrix Math. Basic Matrix Operations. Solving Systems of

More information

Section V.3: Dot Product

Section V.3: Dot Product Section V.3: Dot Product Introduction So far we have looked at operations on a single vector. There are a number of ways to combine two vectors. Vector addition and subtraction will not be covered here,

More information

Solution to Homework 2

Solution to Homework 2 Solution to Homework 2 Olena Bormashenko September 23, 2011 Section 1.4: 1(a)(b)(i)(k), 4, 5, 14; Section 1.5: 1(a)(b)(c)(d)(e)(n), 2(a)(c), 13, 16, 17, 18, 27 Section 1.4 1. Compute the following, if

More information

Beginner s Matlab Tutorial

Beginner s Matlab Tutorial Christopher Lum lum@u.washington.edu Introduction Beginner s Matlab Tutorial This document is designed to act as a tutorial for an individual who has had no prior experience with Matlab. For any questions

More information

Lecture 2 Matrix Operations

Lecture 2 Matrix Operations Lecture 2 Matrix Operations transpose, sum & difference, scalar multiplication matrix multiplication, matrix-vector product matrix inverse 2 1 Matrix transpose transpose of m n matrix A, denoted A T or

More information

Lecture Notes 2: Matrices as Systems of Linear Equations

Lecture Notes 2: Matrices as Systems of Linear Equations 2: Matrices as Systems of Linear Equations 33A Linear Algebra, Puck Rombach Last updated: April 13, 2016 Systems of Linear Equations Systems of linear equations can represent many things You have probably

More information

Excel Basics By Tom Peters & Laura Spielman

Excel Basics By Tom Peters & Laura Spielman Excel Basics By Tom Peters & Laura Spielman What is Excel? Microsoft Excel is a software program with spreadsheet format enabling the user to organize raw data, make tables and charts, graph and model

More information

[1] Diagonal factorization

[1] Diagonal factorization 8.03 LA.6: Diagonalization and Orthogonal Matrices [ Diagonal factorization [2 Solving systems of first order differential equations [3 Symmetric and Orthonormal Matrices [ Diagonal factorization Recall:

More information

Matrix Algebra in R A Minimal Introduction

Matrix Algebra in R A Minimal Introduction A Minimal Introduction James H. Steiger Department of Psychology and Human Development Vanderbilt University Regression Modeling, 2009 1 Defining a Matrix in R Entering by Columns Entering by Rows Entering

More information

13 MATH FACTS 101. 2 a = 1. 7. The elements of a vector have a graphical interpretation, which is particularly easy to see in two or three dimensions.

13 MATH FACTS 101. 2 a = 1. 7. The elements of a vector have a graphical interpretation, which is particularly easy to see in two or three dimensions. 3 MATH FACTS 0 3 MATH FACTS 3. Vectors 3.. Definition We use the overhead arrow to denote a column vector, i.e., a linear segment with a direction. For example, in three-space, we write a vector in terms

More information

The Projection Matrix

The Projection Matrix The Projection Matrix David Arnold Fall 996 Abstract In this activity you will use Matlab to project a set of vectors onto a single vector. Prerequisites. Inner product (dot product) and orthogonal vectors.

More information

Solving Mass Balances using Matrix Algebra

Solving Mass Balances using Matrix Algebra Page: 1 Alex Doll, P.Eng, Alex G Doll Consulting Ltd. http://www.agdconsulting.ca Abstract Matrix Algebra, also known as linear algebra, is well suited to solving material balance problems encountered

More information

Linear Algebra and TI 89

Linear Algebra and TI 89 Linear Algebra and TI 89 Abdul Hassen and Jay Schiffman This short manual is a quick guide to the use of TI89 for Linear Algebra. We do this in two sections. In the first section, we will go over the editing

More information

A linear combination is a sum of scalars times quantities. Such expressions arise quite frequently and have the form

A linear combination is a sum of scalars times quantities. Such expressions arise quite frequently and have the form Section 1.3 Matrix Products A linear combination is a sum of scalars times quantities. Such expressions arise quite frequently and have the form (scalar #1)(quantity #1) + (scalar #2)(quantity #2) +...

More information

Using Casio Graphics Calculators

Using Casio Graphics Calculators Using Casio Graphics Calculators (Some of this document is based on papers prepared by Donald Stover in January 2004.) This document summarizes calculation and programming operations with many contemporary

More information

a(1) = first.entry of a

a(1) = first.entry of a Lecture 2 vectors and matrices ROW VECTORS Enter the following in SciLab: [1,2,3] scilab notation for row vectors [8]==8 a=[2 3 4] separate entries with spaces or commas b=[10,10,10] a+b, b-a add, subtract

More information

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS. + + x 2. x n. a 11 a 12 a 1n b 1 a 21 a 22 a 2n b 2 a 31 a 32 a 3n b 3. a m1 a m2 a mn b m

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS. + + x 2. x n. a 11 a 12 a 1n b 1 a 21 a 22 a 2n b 2 a 31 a 32 a 3n b 3. a m1 a m2 a mn b m MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS 1. SYSTEMS OF EQUATIONS AND MATRICES 1.1. Representation of a linear system. The general system of m equations in n unknowns can be written a 11 x 1 + a 12 x 2 +

More information

Matrices 2. Solving Square Systems of Linear Equations; Inverse Matrices

Matrices 2. Solving Square Systems of Linear Equations; Inverse Matrices Matrices 2. Solving Square Systems of Linear Equations; Inverse Matrices Solving square systems of linear equations; inverse matrices. Linear algebra is essentially about solving systems of linear equations,

More information

MATHEMATICS FOR ENGINEERS BASIC MATRIX THEORY TUTORIAL 2

MATHEMATICS FOR ENGINEERS BASIC MATRIX THEORY TUTORIAL 2 MATHEMATICS FO ENGINEES BASIC MATIX THEOY TUTOIAL This is the second of two tutorials on matrix theory. On completion you should be able to do the following. Explain the general method for solving simultaneous

More information

1 Introduction to Matrices

1 Introduction to Matrices 1 Introduction to Matrices In this section, important definitions and results from matrix algebra that are useful in regression analysis are introduced. While all statements below regarding the columns

More information

How long is the vector? >> length(x) >> d=size(x) % What are the entries in the matrix d?

How long is the vector? >> length(x) >> d=size(x) % What are the entries in the matrix d? MATLAB : A TUTORIAL 1. Creating vectors..................................... 2 2. Evaluating functions y = f(x), manipulating vectors. 4 3. Plotting............................................ 5 4. Miscellaneous

More information

Solving simultaneous equations using the inverse matrix

Solving simultaneous equations using the inverse matrix Solving simultaneous equations using the inverse matrix 8.2 Introduction The power of matrix algebra is seen in the representation of a system of simultaneous linear equations as a matrix equation. Matrix

More information

Notes on Orthogonal and Symmetric Matrices MENU, Winter 2013

Notes on Orthogonal and Symmetric Matrices MENU, Winter 2013 Notes on Orthogonal and Symmetric Matrices MENU, Winter 201 These notes summarize the main properties and uses of orthogonal and symmetric matrices. We covered quite a bit of material regarding these topics,

More information

MATLAB Functions. function [Out_1,Out_2,,Out_N] = function_name(in_1,in_2,,in_m)

MATLAB Functions. function [Out_1,Out_2,,Out_N] = function_name(in_1,in_2,,in_m) MATLAB Functions What is a MATLAB function? A MATLAB function is a MATLAB program that performs a sequence of operations specified in a text file (called an m-file because it must be saved with a file

More information

DETERMINANTS TERRY A. LORING

DETERMINANTS TERRY A. LORING DETERMINANTS TERRY A. LORING 1. Determinants: a Row Operation By-Product The determinant is best understood in terms of row operations, in my opinion. Most books start by defining the determinant via formulas

More information

CS3220 Lecture Notes: QR factorization and orthogonal transformations

CS3220 Lecture Notes: QR factorization and orthogonal transformations CS3220 Lecture Notes: QR factorization and orthogonal transformations Steve Marschner Cornell University 11 March 2009 In this lecture I ll talk about orthogonal matrices and their properties, discuss

More information

Rotation Matrices and Homogeneous Transformations

Rotation Matrices and Homogeneous Transformations Rotation Matrices and Homogeneous Transformations A coordinate frame in an n-dimensional space is defined by n mutually orthogonal unit vectors. In particular, for a two-dimensional (2D) space, i.e., n

More information

SYSTEMS OF EQUATIONS AND MATRICES WITH THE TI-89. by Joseph Collison

SYSTEMS OF EQUATIONS AND MATRICES WITH THE TI-89. by Joseph Collison SYSTEMS OF EQUATIONS AND MATRICES WITH THE TI-89 by Joseph Collison Copyright 2000 by Joseph Collison All rights reserved Reproduction or translation of any part of this work beyond that permitted by Sections

More information

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS Systems of Equations and Matrices Representation of a linear system The general system of m equations in n unknowns can be written a x + a 2 x 2 + + a n x n b a

More information

K80TTQ1EP-??,VO.L,XU0H5BY,_71ZVPKOE678_X,N2Y-8HI4VS,,6Z28DDW5N7ADY013

K80TTQ1EP-??,VO.L,XU0H5BY,_71ZVPKOE678_X,N2Y-8HI4VS,,6Z28DDW5N7ADY013 Hill Cipher Project K80TTQ1EP-??,VO.L,XU0H5BY,_71ZVPKOE678_X,N2Y-8HI4VS,,6Z28DDW5N7ADY013 Directions: Answer all numbered questions completely. Show non-trivial work in the space provided. Non-computational

More information

EXCEL SOLVER TUTORIAL

EXCEL SOLVER TUTORIAL ENGR62/MS&E111 Autumn 2003 2004 Prof. Ben Van Roy October 1, 2003 EXCEL SOLVER TUTORIAL This tutorial will introduce you to some essential features of Excel and its plug-in, Solver, that we will be using

More information

December 4, 2013 MATH 171 BASIC LINEAR ALGEBRA B. KITCHENS

December 4, 2013 MATH 171 BASIC LINEAR ALGEBRA B. KITCHENS December 4, 2013 MATH 171 BASIC LINEAR ALGEBRA B KITCHENS The equation 1 Lines in two-dimensional space (1) 2x y = 3 describes a line in two-dimensional space The coefficients of x and y in the equation

More information

Excel supplement: Chapter 7 Matrix and vector algebra

Excel supplement: Chapter 7 Matrix and vector algebra Excel supplement: Chapter 7 atrix and vector algebra any models in economics lead to large systems of linear equations. These problems are particularly suited for computers. The main purpose of this chapter

More information

Linear Programming. March 14, 2014

Linear Programming. March 14, 2014 Linear Programming March 1, 01 Parts of this introduction to linear programming were adapted from Chapter 9 of Introduction to Algorithms, Second Edition, by Cormen, Leiserson, Rivest and Stein [1]. 1

More information

Linear Algebra Review. Vectors

Linear Algebra Review. Vectors Linear Algebra Review By Tim K. Marks UCSD Borrows heavily from: Jana Kosecka kosecka@cs.gmu.edu http://cs.gmu.edu/~kosecka/cs682.html Virginia de Sa Cogsci 8F Linear Algebra review UCSD Vectors The length

More information

WESTMORELAND COUNTY PUBLIC SCHOOLS 2011 2012 Integrated Instructional Pacing Guide and Checklist Computer Math

WESTMORELAND COUNTY PUBLIC SCHOOLS 2011 2012 Integrated Instructional Pacing Guide and Checklist Computer Math Textbook Correlation WESTMORELAND COUNTY PUBLIC SCHOOLS 2011 2012 Integrated Instructional Pacing Guide and Checklist Computer Math Following Directions Unit FIRST QUARTER AND SECOND QUARTER Logic Unit

More information

8.2. Solution by Inverse Matrix Method. Introduction. Prerequisites. Learning Outcomes

8.2. Solution by Inverse Matrix Method. Introduction. Prerequisites. Learning Outcomes Solution by Inverse Matrix Method 8.2 Introduction The power of matrix algebra is seen in the representation of a system of simultaneous linear equations as a matrix equation. Matrix algebra allows us

More information

Here are some examples of combining elements and the operations used:

Here are some examples of combining elements and the operations used: MATRIX OPERATIONS Summary of article: What is an operation? Addition of two matrices. Multiplication of a Matrix by a scalar. Subtraction of two matrices: two ways to do it. Combinations of Addition, Subtraction,

More information

9.4. The Scalar Product. Introduction. Prerequisites. Learning Style. Learning Outcomes

9.4. The Scalar Product. Introduction. Prerequisites. Learning Style. Learning Outcomes The Scalar Product 9.4 Introduction There are two kinds of multiplication involving vectors. The first is known as the scalar product or dot product. This is so-called because when the scalar product of

More information

Introduction to Matrix Algebra

Introduction to Matrix Algebra Psychology 7291: Multivariate Statistics (Carey) 8/27/98 Matrix Algebra - 1 Introduction to Matrix Algebra Definitions: A matrix is a collection of numbers ordered by rows and columns. It is customary

More information

Question 2: How do you solve a matrix equation using the matrix inverse?

Question 2: How do you solve a matrix equation using the matrix inverse? Question : How do you solve a matrix equation using the matrix inverse? In the previous question, we wrote systems of equations as a matrix equation AX B. In this format, the matrix A contains the coefficients

More information

Estimating a market model: Step-by-step Prepared by Pamela Peterson Drake Florida Atlantic University

Estimating a market model: Step-by-step Prepared by Pamela Peterson Drake Florida Atlantic University Estimating a market model: Step-by-step Prepared by Pamela Peterson Drake Florida Atlantic University The purpose of this document is to guide you through the process of estimating a market model for the

More information

Doing Multiple Regression with SPSS. In this case, we are interested in the Analyze options so we choose that menu. If gives us a number of choices:

Doing Multiple Regression with SPSS. In this case, we are interested in the Analyze options so we choose that menu. If gives us a number of choices: Doing Multiple Regression with SPSS Multiple Regression for Data Already in Data Editor Next we want to specify a multiple regression analysis for these data. The menu bar for SPSS offers several options:

More information

Introduction to Matrices

Introduction to Matrices Introduction to Matrices Tom Davis tomrdavis@earthlinknet 1 Definitions A matrix (plural: matrices) is simply a rectangular array of things For now, we ll assume the things are numbers, but as you go on

More information

Math 1050 Khan Academy Extra Credit Algebra Assignment

Math 1050 Khan Academy Extra Credit Algebra Assignment Math 1050 Khan Academy Extra Credit Algebra Assignment KhanAcademy.org offers over 2,700 instructional videos, including hundreds of videos teaching algebra concepts, and corresponding problem sets. In

More information

PLOTTING DATA AND INTERPRETING GRAPHS

PLOTTING DATA AND INTERPRETING GRAPHS PLOTTING DATA AND INTERPRETING GRAPHS Fundamentals of Graphing One of the most important sets of skills in science and mathematics is the ability to construct graphs and to interpret the information they

More information

Brief Introduction to Vectors and Matrices

Brief Introduction to Vectors and Matrices CHAPTER 1 Brief Introduction to Vectors and Matrices In this chapter, we will discuss some needed concepts found in introductory course in linear algebra. We will introduce matrix, vector, vector-valued

More information

Vectors 2. The METRIC Project, Imperial College. Imperial College of Science Technology and Medicine, 1996.

Vectors 2. The METRIC Project, Imperial College. Imperial College of Science Technology and Medicine, 1996. Vectors 2 The METRIC Project, Imperial College. Imperial College of Science Technology and Medicine, 1996. Launch Mathematica. Type

More information

Lecture 3: Finding integer solutions to systems of linear equations

Lecture 3: Finding integer solutions to systems of linear equations Lecture 3: Finding integer solutions to systems of linear equations Algorithmic Number Theory (Fall 2014) Rutgers University Swastik Kopparty Scribe: Abhishek Bhrushundi 1 Overview The goal of this lecture

More information

Introduction to Matrices for Engineers

Introduction to Matrices for Engineers Introduction to Matrices for Engineers C.T.J. Dodson, School of Mathematics, Manchester Universit 1 What is a Matrix? A matrix is a rectangular arra of elements, usuall numbers, e.g. 1 0-8 4 0-1 1 0 11

More information

28 CHAPTER 1. VECTORS AND THE GEOMETRY OF SPACE. v x. u y v z u z v y u y u z. v y v z

28 CHAPTER 1. VECTORS AND THE GEOMETRY OF SPACE. v x. u y v z u z v y u y u z. v y v z 28 CHAPTER 1. VECTORS AND THE GEOMETRY OF SPACE 1.4 Cross Product 1.4.1 Definitions The cross product is the second multiplication operation between vectors we will study. The goal behind the definition

More information

DERIVATIVES AS MATRICES; CHAIN RULE

DERIVATIVES AS MATRICES; CHAIN RULE DERIVATIVES AS MATRICES; CHAIN RULE 1. Derivatives of Real-valued Functions Let s first consider functions f : R 2 R. Recall that if the partial derivatives of f exist at the point (x 0, y 0 ), then we

More information

1.2 Solving a System of Linear Equations

1.2 Solving a System of Linear Equations 1.. SOLVING A SYSTEM OF LINEAR EQUATIONS 1. Solving a System of Linear Equations 1..1 Simple Systems - Basic De nitions As noticed above, the general form of a linear system of m equations in n variables

More information

Solutions to Math 51 First Exam January 29, 2015

Solutions to Math 51 First Exam January 29, 2015 Solutions to Math 5 First Exam January 29, 25. ( points) (a) Complete the following sentence: A set of vectors {v,..., v k } is defined to be linearly dependent if (2 points) there exist c,... c k R, not

More information

MATLAB Workshop 3 - Vectors in MATLAB

MATLAB Workshop 3 - Vectors in MATLAB MATLAB: Workshop - Vectors in MATLAB page 1 MATLAB Workshop - Vectors in MATLAB Objectives: Learn about vector properties in MATLAB, methods to create row and column vectors, mathematical functions with

More information

Syntax Description Remarks and examples Also see

Syntax Description Remarks and examples Also see Title stata.com permutation An aside on permutation matrices and vectors Syntax Description Remarks and examples Also see Syntax Permutation matrix Permutation vector Action notation notation permute rows

More information

Linear Algebra: Vectors

Linear Algebra: Vectors A Linear Algebra: Vectors A Appendix A: LINEAR ALGEBRA: VECTORS TABLE OF CONTENTS Page A Motivation A 3 A2 Vectors A 3 A2 Notational Conventions A 4 A22 Visualization A 5 A23 Special Vectors A 5 A3 Vector

More information

Linear Algebra Notes for Marsden and Tromba Vector Calculus

Linear Algebra Notes for Marsden and Tromba Vector Calculus Linear Algebra Notes for Marsden and Tromba Vector Calculus n-dimensional Euclidean Space and Matrices Definition of n space As was learned in Math b, a point in Euclidean three space can be thought of

More information

u = [ 2 4 5] has one row with three components (a 3 v = [2 4 5] has three rows separated by semicolons (a 3 w = 2:5 generates the row vector w = [ 2 3

u = [ 2 4 5] has one row with three components (a 3 v = [2 4 5] has three rows separated by semicolons (a 3 w = 2:5 generates the row vector w = [ 2 3 MATLAB Tutorial You need a small numb e r of basic commands to start using MATLAB. This short tutorial describes those fundamental commands. You need to create vectors and matrices, to change them, and

More information

MATLAB Basics MATLAB numbers and numeric formats

MATLAB Basics MATLAB numbers and numeric formats MATLAB Basics MATLAB numbers and numeric formats All numerical variables are stored in MATLAB in double precision floating-point form. (In fact it is possible to force some variables to be of other types

More information

Using Microsoft Excel Built-in Functions and Matrix Operations. EGN 1006 Introduction to the Engineering Profession

Using Microsoft Excel Built-in Functions and Matrix Operations. EGN 1006 Introduction to the Engineering Profession Using Microsoft Ecel Built-in Functions and Matri Operations EGN 006 Introduction to the Engineering Profession Ecel Embedded Functions Ecel has a wide variety of Built-in Functions: Mathematical Financial

More information

Solving Systems of Linear Equations Using Matrices

Solving Systems of Linear Equations Using Matrices Solving Systems of Linear Equations Using Matrices What is a Matrix? A matrix is a compact grid or array of numbers. It can be created from a system of equations and used to solve the system of equations.

More information

Matrix Differentiation

Matrix Differentiation 1 Introduction Matrix Differentiation ( and some other stuff ) Randal J. Barnes Department of Civil Engineering, University of Minnesota Minneapolis, Minnesota, USA Throughout this presentation I have

More information

Introduction to Matlab

Introduction to Matlab Introduction to Matlab Social Science Research Lab American University, Washington, D.C. Web. www.american.edu/provost/ctrl/pclabs.cfm Tel. x3862 Email. SSRL@American.edu Course Objective This course provides

More information

CBE 6333, R. Levicky 1. Tensor Notation.

CBE 6333, R. Levicky 1. Tensor Notation. CBE 6333, R. Levicky 1 Tensor Notation. Engineers and scientists find it useful to have a general terminology to indicate how many directions are associated with a physical quantity such as temperature

More information

Chapter 4. Spreadsheets

Chapter 4. Spreadsheets Chapter 4. Spreadsheets We ve discussed rather briefly the use of computer algebra in 3.5. The approach of relying on www.wolframalpha.com is a poor subsititute for a fullfeatured computer algebra program

More information

Vector Math Computer Graphics Scott D. Anderson

Vector Math Computer Graphics Scott D. Anderson Vector Math Computer Graphics Scott D. Anderson 1 Dot Product The notation v w means the dot product or scalar product or inner product of two vectors, v and w. In abstract mathematics, we can talk about

More information

Summary of important mathematical operations and formulas (from first tutorial):

Summary of important mathematical operations and formulas (from first tutorial): EXCEL Intermediate Tutorial Summary of important mathematical operations and formulas (from first tutorial): Operation Key Addition + Subtraction - Multiplication * Division / Exponential ^ To enter a

More information

Determine If An Equation Represents a Function

Determine If An Equation Represents a Function Question : What is a linear function? The term linear function consists of two parts: linear and function. To understand what these terms mean together, we must first understand what a function is. The

More information

Torgerson s Classical MDS derivation: 1: Determining Coordinates from Euclidean Distances

Torgerson s Classical MDS derivation: 1: Determining Coordinates from Euclidean Distances Torgerson s Classical MDS derivation: 1: Determining Coordinates from Euclidean Distances It is possible to construct a matrix X of Cartesian coordinates of points in Euclidean space when we know the Euclidean

More information

Review Jeopardy. Blue vs. Orange. Review Jeopardy

Review Jeopardy. Blue vs. Orange. Review Jeopardy Review Jeopardy Blue vs. Orange Review Jeopardy Jeopardy Round Lectures 0-3 Jeopardy Round $200 How could I measure how far apart (i.e. how different) two observations, y 1 and y 2, are from each other?

More information

Math 2524: Activity 3 (Excel and Matrices, continued) Fall 2002

Math 2524: Activity 3 (Excel and Matrices, continued) Fall 2002 Inverse of a Matrix: This activity will illustrate how Excel can help you find and use the inverse of a matrix. It will also discuss a matrix function called the determinant and a method called Cramer's

More information

Situation Analysis. Example! See your Industry Conditions Report for exact information. 1 Perceptual Map

Situation Analysis. Example! See your Industry Conditions Report for exact information. 1 Perceptual Map Perceptual Map Situation Analysis The Situation Analysis will help your company understand current market conditions and how the industry will evolve over the next eight years. The analysis can be done

More information

5 Homogeneous systems

5 Homogeneous systems 5 Homogeneous systems Definition: A homogeneous (ho-mo-jeen -i-us) system of linear algebraic equations is one in which all the numbers on the right hand side are equal to : a x +... + a n x n =.. a m

More information

A Primer on Index Notation

A Primer on Index Notation A Primer on John Crimaldi August 28, 2006 1. Index versus Index notation (a.k.a. Cartesian notation) is a powerful tool for manipulating multidimensional equations. However, there are times when the more

More information

Factoring. Factoring Monomials Monomials can often be factored in more than one way.

Factoring. Factoring Monomials Monomials can often be factored in more than one way. Factoring Factoring is the reverse of multiplying. When we multiplied monomials or polynomials together, we got a new monomial or a string of monomials that were added (or subtracted) together. For example,

More information

Excel Formatting: Best Practices in Financial Models

Excel Formatting: Best Practices in Financial Models Excel Formatting: Best Practices in Financial Models Properly formatting your Excel models is important because it makes it easier for others to read and understand your analysis and for you to read and

More information

Tool 1. Greatest Common Factor (GCF)

Tool 1. Greatest Common Factor (GCF) Chapter 4: Factoring Review Tool 1 Greatest Common Factor (GCF) This is a very important tool. You must try to factor out the GCF first in every problem. Some problems do not have a GCF but many do. When

More information

10. Comparing Means Using Repeated Measures ANOVA

10. Comparing Means Using Repeated Measures ANOVA 10. Comparing Means Using Repeated Measures ANOVA Objectives Calculate repeated measures ANOVAs Calculate effect size Conduct multiple comparisons Graphically illustrate mean differences Repeated measures

More information

Similarity and Diagonalization. Similar Matrices

Similarity and Diagonalization. Similar Matrices MATH022 Linear Algebra Brief lecture notes 48 Similarity and Diagonalization Similar Matrices Let A and B be n n matrices. We say that A is similar to B if there is an invertible n n matrix P such that

More information

WEEK #3, Lecture 1: Sparse Systems, MATLAB Graphics

WEEK #3, Lecture 1: Sparse Systems, MATLAB Graphics WEEK #3, Lecture 1: Sparse Systems, MATLAB Graphics Visualization of Matrices Good visuals anchor any presentation. MATLAB has a wide variety of ways to display data and calculation results that can be

More information

Continued Fractions and the Euclidean Algorithm

Continued Fractions and the Euclidean Algorithm Continued Fractions and the Euclidean Algorithm Lecture notes prepared for MATH 326, Spring 997 Department of Mathematics and Statistics University at Albany William F Hammond Table of Contents Introduction

More information

2x + y = 3. Since the second equation is precisely the same as the first equation, it is enough to find x and y satisfying the system

2x + y = 3. Since the second equation is precisely the same as the first equation, it is enough to find x and y satisfying the system 1. Systems of linear equations We are interested in the solutions to systems of linear equations. A linear equation is of the form 3x 5y + 2z + w = 3. The key thing is that we don t multiply the variables

More information

To give it a definition, an implicit function of x and y is simply any relationship that takes the form:

To give it a definition, an implicit function of x and y is simply any relationship that takes the form: 2 Implicit function theorems and applications 21 Implicit functions The implicit function theorem is one of the most useful single tools you ll meet this year After a while, it will be second nature to

More information

LS.6 Solution Matrices

LS.6 Solution Matrices LS.6 Solution Matrices In the literature, solutions to linear systems often are expressed using square matrices rather than vectors. You need to get used to the terminology. As before, we state the definitions

More information

8 Square matrices continued: Determinants

8 Square matrices continued: Determinants 8 Square matrices continued: Determinants 8. Introduction Determinants give us important information about square matrices, and, as we ll soon see, are essential for the computation of eigenvalues. You

More information

AP Computer Science Java Mr. Clausen Program 9A, 9B

AP Computer Science Java Mr. Clausen Program 9A, 9B AP Computer Science Java Mr. Clausen Program 9A, 9B PROGRAM 9A I m_sort_of_searching (20 points now, 60 points when all parts are finished) The purpose of this project is to set up a program that will

More information

Vectors Math 122 Calculus III D Joyce, Fall 2012

Vectors Math 122 Calculus III D Joyce, Fall 2012 Vectors Math 122 Calculus III D Joyce, Fall 2012 Vectors in the plane R 2. A vector v can be interpreted as an arro in the plane R 2 ith a certain length and a certain direction. The same vector can be

More information

Tutorial for the TI-89 Titanium Calculator

Tutorial for the TI-89 Titanium Calculator SI Physics Tutorial for the TI-89 Titanium Calculator Using Scientific Notation on a TI-89 Titanium calculator From Home, press the Mode button, then scroll down to Exponential Format. Select Scientific.

More information

1 Review of Least Squares Solutions to Overdetermined Systems

1 Review of Least Squares Solutions to Overdetermined Systems cs4: introduction to numerical analysis /9/0 Lecture 7: Rectangular Systems and Numerical Integration Instructor: Professor Amos Ron Scribes: Mark Cowlishaw, Nathanael Fillmore Review of Least Squares

More information

Excel 2010: Create your first spreadsheet

Excel 2010: Create your first spreadsheet Excel 2010: Create your first spreadsheet Goals: After completing this course you will be able to: Create a new spreadsheet. Add, subtract, multiply, and divide in a spreadsheet. Enter and format column

More information

Multiple regression - Matrices

Multiple regression - Matrices Multiple regression - Matrices This handout will present various matrices which are substantively interesting and/or provide useful means of summarizing the data for analytical purposes. As we will see,

More information

Dynamic Programming. Lecture 11. 11.1 Overview. 11.2 Introduction

Dynamic Programming. Lecture 11. 11.1 Overview. 11.2 Introduction Lecture 11 Dynamic Programming 11.1 Overview Dynamic Programming is a powerful technique that allows one to solve many different types of problems in time O(n 2 ) or O(n 3 ) for which a naive approach

More information