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Grading: The course % for M442 is 
Homework: Assigned homework Handouts: PDF handouts will either 
Rough Syllabus: (select topics from the chapters listed below)
 Chapter 4: Interpolation and Numerical Differentiation

Chapter 5: Numerical Integration
 Chapter 7: Initial Value Problems

Chapter 11: Boundary Value Problems

Chapter 12: Partial Differential Equations
Attendance in class is paramount to knowing which subtopics of each chapter will be covered!
In class I may cover the topics in a manner different from the textbook.
Matlab code for M442:
Code to interpolate data X with functions phi(x,n)  
ld.m  Code declaring cardinal polynomials as a function ld(i,x,X), where X=data x values  
cardinal.m  Code for polynomial interpolation using cardinal polynomials in ld.m  
Matlab code for M441:
Df_procedure.m  secant approximation for derivative of sin(x)  
Df.m  Df_procedure declared as a function  
Horner.m  Method for fast polynomial evaluation  
f.m  a function for Bisect.m  
g.m  a different function for Bisect.m  
Bisect.m  Bisection Method  
BisectF.m  Bisection Method: fancy version  
f.m  a function for Newton.m  
df.m  the derivative of f(x) in f.m  
Newton.m  Newton's method  
NewtonPlot.m  plots tangent lines in Newton method.  
Secant.m  Secant Method  
GaussNaive.m  Gauss step by step solver  
Elementary.m  Elementary matrices and LU decomp. Needs this too: Elem.m  
phi.m  Power Method Selector function  
Power.m  Power method example  
Iterate.m  Richardson, Jacobi, GausSeidel, SOR iterative methods 
Matlab links:
getting matlab 
a link to downloading matlab on MSU campus. You will need 

intro  of campus link with simple introduction to syntax in matlab  
mathworks  company that develops and maintains matlab 
To download/install/use matlab you'll need your first.last@ecat1.montana.edu campus email.

Learing outcome Numerical integration, numerical solutions of initial and boundary value problems in ordinary differential equations. Numerical solutions of partial differential equations.