Mathematics is a natural language for quantifying and codifying thoughts and ideas. It is also a language of precision and logic. Just as pictures or words can be used to describe objects or actions, so too can mathematical models be used as a basis for an idealized or abstract understanding. This course will explore the concepts of mathematical models by utilizing the numerical and algorithmic nature of computers.
Lectures and labs will be based upon a case-study approach of various themes in mathematical modelling. Among the types of models to be presented are: dynamical systems, random processes and statistical data sets. The rudiments of computation and simulation and graphical presentation will be developed through the use of the Matlab and Maple computing environments.
assignment lab help walkthroughs 3:30-5:00pm lab report instructions (pdf) the starred points in the worksheet can be worked on in advance of the tutorial session lab worksheet (w1curve.txt) contour integration lab (w1curve.m) contour function (w1curve1.m) integrand function (w1curve2.m) first lab tutorial, room AQ3148B (PC lab) arrange to have a lab partner bring a lab notebook lab scripts to be posted soon Simpson's rule sample lab
sample worksheet (w1simp.txt) simpson's rule demo (w1simp.m) integrand (w1simp1.m) sample report (pdf)
first lecture, room AQ5018 at 1:30pm syllabus (pdf) administrative office hours from 3:30pm bring completed info sheet (pdf) matlab demo for first lecture sample worksheet (w1simp.txt) simpson's rule demo (w1simp.m) integrand (w1simp1.m)
matlab intro manual (pdf) maple web info (link)
abstract (pdf) textbook (a course in mathematical modeling)
matlab intro manual (pdf) maple web info (link) contour integration (link)