This isn’t a math text, nor a statistics text, not a computer science text. It is a text on Computational Science, an interdisciplinary amalgamation of all three.
A course in computational science typically assumes students to have taken calculus and to have programming skills. This book assumes neither, nor is it goal of the text to develop calculus or to turn students into programmers. It is a goal of this text to build skills in computation, specifically computing with and analyzing data using Microsoft Excel and Python. While much of the text is about building skills, some parts are about illustrating a computational journey, thus building a conceptual framework for understanding the big picture.
When it comes to computation, there are often many different approaches that one can take. This text presents approaches that illustrates and reinforces concepts, and makes no attempt at maximizing efficiency. Our goal is to develop and exercise computational thinking, not to minimize computation time or computer memory used.
But, as there are many different ways to approach the computational examples explored in the text, some instructors will show you, out of personal preferences, different ways to solve certain problems. Go with the flow, diversity is a good thing.
This is an alpha-version of the text, so our apologies for anything wanting. Your feedback is welcome and appreciated.