Mathematical Tools at MIT: Introduction to MATLAB
On this page:
Overview
Class Materials
Overview
The following materials were originally developed for a hands-on training course offered by the Office of Educational Innovation and Technology (OEIT) during the Independent Activities Period in January. The exercise topics (e.g. linear equations, curve fitting, graphics, etc.) are designed to be applicable to many disciplines.
MIT students, other members of the MIT community, and the general public may use these materials as a standalone tutorial. They are made available to the MIT community and the general public under the Attribution-Noncommercial-Share Alike 3.0 United States license.
Class Materials
Every session has a handout with instructions in PDF format. The handout summarizes MATLAB concepts, functions, and programming routines that are introduced and/or practiced in the session.
Note:
- Some exercises in sessions 2, 3, 4, 5, and 6 build on exercises that have been completed in previous sessions.
- Using MATLAB requires a good knowledge of matrix mathematics (at least 18.02 or equivalent).
- Additional mathematics backgroud is recommended (e.g., 18.03 for Session 2; 18.05 for Session 6).
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Session
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Description
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Handouts (PDF)
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Exercises and Demos (M-Files)
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1. MATLAB User Interface and Basics |
Desktop interface, toolboxes, variables, vectors, matrices, operators, built-in functions, input and output. |
InterfaceBasics.zip (archive) or |
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2. Calculus, Linear Algebra, ODEs |
Polynomials, integration, curve fitting, linear systems of equations, convolution, differential equations. |
LinsysCalcODE.zip (archive) or |
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3. Graphics and Visualization |
2D and 3D plotting functions, graphics customizations, property editor, figure and axes handles, animation. |
Graphics.zip (archive) or |
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4. Basic Programming |
Function and script m-files, data types, strings, relational and logical operators, program flow control, debugging. |
Programming.zip (archive) or |
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5. Programming Practice |
GUIDE editor, graphical user interface programming, callbacks, MATLAB File Exchange. |
Practice.zip (archive) or |
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6. Statistics and Data Analysis |
Probability distributions, linear models, regression, confidence intervals, graphical representation, ANOVA. |
Statistics.zip (archive) or |
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Solutions |
Exercise solutions for all sessions. |
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solutions.zip (archive) or |
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