MA 334

Differential Equations, Linear Algebra,
and
Probability and Statistics

Mark Parker

MWF, 2:00 - 2:50, Simperman 123

T, 9:30 - 10:45, Simperman 123

Th, 9:30 - 10:45, Simperman 146

Introduction

We will start this course by looking at differential equations. After a quick review, we'll explore applications involving the solution of second order linear differential equations with constant coefficients. Such equations are then viewed in their relationship to selected partial differential equations with both initial and boundary values conditions. Second order equations are extended to systems of linear differential equations, which we'll tie back to systems of difference equations and solve with a formal linear algebra approach using eigenvalues and eigenvectors. We will extend these linear systems of differential equations into the nonlinear realm, where we look at linearization as a simplifying tool. On the linear algebra front, we will formalize our explorations of vector spaces, spanning sets, and, linear transformations. The last portion of the class is spent on probability and statistics with an emphasis on exploratory data analysis and applications involving selected distributions and reliability analysis.

We will continue our threaded approach to learning mathematics by exploring differential equations from a linear algebra perspective. In our journey, we will make use of both the calculator and Mathematica. We will expand our computing tool repertoire by using Excel and SPSS as we explore probability and statistics.

Texts

	Differential Equations and Linear Algebra, First Edition	Farlow, Hall, McDill, and West	Prentice Hall
	Applied Statistics and Probability for Engineers Third Edition	Montgomery and Runger	John Wiley and Sons

Grading

Your grade will translate to a letter grade as follows :

• A 90% or better
• B 80% or better
• C 70% or better
• D 60% or better
• F otherwise