Loading...

MA213: Numerical Analysis

Course Syllabus for "MA213: Numerical Analysis"

Numerical analysis is the study of the methods used to solve problems involving continuous variables.  It is a highly applied branch of mathematics and computer science, wherein abstract ideas and theories become the quantities describing things we can actually touch and see.  The real number line is an abstraction where many interesting and useful ideas live, but to actually realize these ideas, we are forced to employ approximations of the real numbers.  For example, consider marking a ruler at \sqrt{2}.  We know that \sqrt{2} \approx 1.4142, but if we put the mark there, we know we are in error for there is an infinite sequence of nonzero digits following the 2.  Even more: a number doesn’t have any width, yet any mark we make would have a width, and in that width lives an infinite number of real numbers.  You may ask yourself: isn’t it sufficient to represent \sqrt{2} with 1.414?  This is the kind of question that this course will explore.  We have been trying to answer such questions for over 2,000 years (it is said that people have given their lives for the idea of \sqrt{2}, and they certainly wouldn’t think 1.414 sufficient).  Modern computers can perform billions of arithmetic operations per second and trying to predict the path of a tropical storm can require many trillions of operations.  How do we carry out such simulations and how do our approximations affect the result?  The answer to the first question is certainly colored by the second! Numerical analysis is a broad and growing discipline with many open questions.  This course is designed to be a first look at the discipline.  Over the course of this semester, we will survey some of the basic problems and methods needed to simulate the solutions of ordinary differential equations.  We will build the methods ourselves, starting with computer arithmetic, so that you will understand all of the pieces and how they fit together in state of the art algorithms.  Along the way, we will write programs to solve equations, plot curves, integrate functions, and solve initial value problems.  At the end of some chapters we will suggest - in a section called “Of Things Not Covered” - some topics that would have been included if we had more time or other avenues to explore if you are interested in the topics presented in the unit. The prerequisites for taking this course are MA211: Linear Algebra, MA221: Differential Equations, and either MA302/CS101: Introduction to Computer Science or a background in some programming language.  Programming ideas will be illustrated in pseudocode and implemented in the open-source high-level computing environment. Numerical Analysis is the field of mathematics that applies numerical approximations in order to solve mathematical problems of continuous variables.In most cases, numerical analysis does not have the goal of finding exact answers to complex problems, as most mathematical problems cannot be solved through the application of a finite number of elementary mathematical operations.Rather, numerical analysis focuses on the development and study of algorithms that will quickly obtain approximate solutions.By analyzing these algorithms, we can evaluate their errors and stability and in turn decide when it is safe to use a particular numerical algorithm.

The first known application of the methods of numerical analysis appears on Babylonian tablet YBC 7289, which is roughly dated between 1700-2000 BC.(Evidence suggests that the writer was a mathematics student.)The tablet features an incised square whose sides have a length of 0.5 units and a diagonal line that connects opposite corners of the square.The diagonal line is labeled 0:42 25 35 (in sexagesimal notation), which tells us that the Babylonians thought that the square root of 2 is 1.41421296 (in decimal notation).(The actual square root of 2 is 1.41421356… to 9 decimal places.)The Babylonian value is in error by roughly 7 parts in 100,000—an accuracy that could not have been obtained by direct measurement.As the square root of 2 is an irrational number, it cannot be directly calculated.Although not known for sure, it is likely that the value for the square root of two was originally calculated by Heron’s method, a simple version of the Newton-Raphson method for finding successively better approximations to the roots of a function.

This course will focus on the applications of the methods of numerical analysis.We will cover enough of the mathematical background to allow you to intelligently discuss the convergence, error, and stability properties of numerical analysis algorithms, but will place emphasis on solving certain classes of problems that often arise in scientific or engineering contexts.These include approximating functions, finding roots of polynomial and other nonlinear functions, solving systems of linear equations, finding eigenvalues and eigenfunctions, optimizing constrained multi-dimensional functions, evaluating integrals, and solving ordinary and partial differential equations.

The prerequisites for taking MA213 are MA211 (Linear Algebra), MA221 (Differential Equations), and either MA302/CS101 (Introduction to Computer Science) or a solid background in JAVA programming.While not necessary, treating MA222 (Partial Differential Equations) as a co-requisite is advised.Many problems and methods will be presented and used within an open-source Java-based computing environment.

Learning Outcomes

 Upon successful completion of this course, the student will be able to:

  • Show how numbers are represented on the computer, and how errors from this representation affect arithmetic. 
  • Analyze errors and have an understanding of error estimation. 
  • Be able to use polynomials in several ways to approximate both functions and data, and to match the type of polynomial approximation to a given type of problem. 
  • Be able to solve equations in one unknown real variable using iterative methods and to understand how long these methods take to converge to a solution. 
  • Derive formulas to approximate the derivative of a function at a point, and formulas to compute the definite integral of a function of one or more variables. 
  • Choose and apply any of several modern methods for solving systems of initial value problems based on properties of the problem.

Course Requirements

In order to take this course you must:
 
√    Have access to a computer.
 
√    Have continuous broadband Internet access.
 
√    Have the ability/permission to install plug-ins or software (e.g., Adobe Reader or Flash).
 
√    Have the ability to download and save files and documents to a computer.
 
√    Have the ability to open Microsoft files and documents (.doc, .ppt, .xls, etc.).
 
√    Be competent in the English language.
     
√    Have read the Saylor Student Handbook.

Course Information

Welcome to MA213 Numerical Analysis.  Below, please find general information on this course and its requirements.

Course Designers: Professor Baccouch
 
Primary Resources: This course primarily relies on content from the following resources:
•       University of Arkansas: Mark Arnold’s “Numerical Analysis Pages”
•       University of Southern Florida: Autar Kaw’s “Numerical Methods Lectures”
 
Requirements for Completion: Viewing videos, reading and working through pages and exercises, and writing 5 programs in Octave.
 
Time Commitment: This course should take about 129 hours to complete.
 
Table of Contents: You can find the course's units at the links below.