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Angelo State University
Mathematical Computing with Python

Mathematical Computing with Python

Last updated

Jan 20, 2023
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- Detailed Licensing
- Front Matter

This page is a draft and is under active development.

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Front Matter
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1: Introduction to Python
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A brief introduction to Python, especially those functions and packages that will be used throughout this text.
2: Monte-Carlo Simulation
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We seek to understand how variations of a system's defining parameters, in particular those composed of a set of static random variables, lead to variations in the system output.
3: Interpolation and Curve Fitting
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Discrete data sets or lists of information are commonly involved in modeling real-world scenarios. The data may come from observations in the field, experimental results, or analytical calculations. In this chapter, we discuss the differences between interpolation and curve fitting and find ways to numerically apply these techniques.
- 3.1: Introduction to Interpolation and Curve Fitting
- 3.2: Polynomial Interpolation
Back Matter
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This book is based on the course notes for Numerical Analysis (Math 4311) at Angelo State University.

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