Holistic Numerical Methods

Transforming Numerical Methods Education for the STEM Undergraduate

 

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WORKSHEETS IN MATHCAD

INTRODUCTION TO SCIENTIFIC COMPUTING

 

Measuring Errors

   

True Error   [MATHCAD]  

Approximate Error   [MATHCAD]

 

Binary Representation

   

Decimal to binary representation  [MATHCAD]  

Binary to decimal representation  [MATHCAD]  

 

Measuring Errors

   

Decimal to floating point representation  [MATHCAD]  

Binary to floating point representation  [MATHCAD]  

 

Propagation of Errors

   

Propagation of Errors   [MATHCAD]  

 

Differentiation

 

Continuous Functions

   

Forward Divided Difference     [MATHCAD]    

Backward Divided Difference    [MATHCAD]    

Central Divided Difference    [MATHCAD]    

Continuous functions Second Order Derivative    [MATHCAD]   

 

Discrete Data

   

Discrete functions    [MATHCAD]   

 

Nonlinear Equations

 

Bisection Method

   

Method  [MATHCAD

Convergence  [MATHCAD

Pitfall: Slow convergence of bisection method simulation  [MATHCAD

 

Newton-Raphson Method

   

Method  [MATHCAD

Convergence  [MATHCAD

Pitfall: Division by zero  [MATHCAD

Pitfall: Slow Convergence at Inflection Points  [MATHCAD

Pitfall: Root jumps over several roots  [MATHCAD

Pitfall: Roots oscillates around local maxima and minima  [MATHCAD

 

Secant Method

   

Simulation of secant method   [MATHCAD

Convergence Simulation of secant method   [MATHCAD

Pitfall: Division by zero in secant method simulation   [MATHCAD

Pitfall: Root jumps over several roots in secant method   [MATHCAD

     

SIMULTANEOUS LINEAR EQUATIONS

 

Gaussian Elimination

   

Method  [MATHCAD

 

Gauss-Seidel Method

   

Method   [MATHCAD]   

   

Convergence   [MATHCAD]   

 

LU Decomposition

   

Method  [MATHCAD

     

Interpolation

 

Direct Method

   

Method  [MATHCAD

 

Newton's Divided Difference Method

   

Method   [MATHCAD]   

 

Lagrange Method

   

Method  [MATHCAD

 

Spline Method

   

Method   [MATHCAD]   

     

REGRESSION

 

Linear Regression

   

Method  [MATHCAD

 

Nonlinear Regression

   

Without Data Linearization   [MATHCAD]   

With Data Linearization   [MATHCAD]   

Polynomial Regression   [MATHCAD]   

Comparing with and without Data Linearization   [MATHCAD]   

 

Adequacy of a Regression Model

   

Adequacy  [MATHCAD

     

Integration

 

Trapezoidal Rule

   

Method  [MATHCAD

Convergence  [MATHCAD

 

Simpson's 1/3rd Rule

   

Method  [MATHCAD

Convergence  [MATHCAD

 

Romberg Rule

   

Method  [MATHCAD

Convergence  [MATHCAD

 

Gauss-Quadrature Rule

   

Method  [MATHCAD

Convergence  [MATHCAD

 

Integrating Discrete Functions

   

Integrating discrete functions  [MATHCAD

 

ORDINARY DIFFERENTIAL EQUATIONS

 

Euler's Method

   

Method  [MATHCAD

Convergence  [MATHCAD

 

Runge-Kutta 2nd order Method

   

Method  [MATHCAD

Convergence  [MATHCAD

 

Runge-Kutta 4th order Method

   

Method  [MATHCAD

Convergence  [MATHCAD

 

Shooting Method

   

Method  [MATHCAD

 

Finite Difference Method

   

Method  [MATHCAD

 


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Copyrights: University of South Florida, 4202 E Fowler Ave, Tampa, FL 33620-5350. All Rights Reserved. Questions, suggestions or comments, contact kaw@eng.usf.edu  This material is based upon work supported by the National Science Foundation under Grant# Creative Commons License0126793, 0341468, 0717624,  0836981, 0836916, 0836805, 1322586.  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.  Other sponsors include Maple, MathCAD, USF, FAMU and MSOE.  Based on a work at http://mathforcollege.com/nm.  Holistic Numerical Methods licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

 

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