Preface & Acknowledgments

This textbook, which was written during the 2020 SARS2 ( AKA COVID-19 ) lockdown, is designed for a higher-level undergraduate course for engineering or science students who are interested to gain knowledge of the underlying mathematical theory of probability. This textbook was designed from the course notes of a course that the author was teaching at Embry Riddle Aeronautical University during the academic terms of the crisis and became the primary reading material for the quickly adapted course in the new online modality. While there is no statistical prerequisite knowledge required to read this book, due to the fact that the study is designed for the reader to truly understand the underlying theory rather than just learn how to read computer output, it would be best read with some familiarity of elementary statistics. However, the book is self-contained, including the optional chapter zero review of descriptive statistics, and the only true prerequisite knowledge is a solid understanding of university level calculus. The intention for this textbook is for an elective type of course; however, the foundations are laid here for further mathematical study and this text could well serve as a transition for an interested student with little to no prior knowledge to then go on to study in the popular fields of data scientist, big data analysts, genetic algorithm designer or whatever the buzz words of the day may call it.

The author is very grateful for the opportunity to have taught the MA 412 course at his current institution and is very thankful to the many students who made corrections along the way. It is to those students, and the future students who will take MA 412, that this book is dedicated to.


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A Self-Contained Course in Mathematical Theory of Probability Copyright © 2024 by Tim Smith and Shannon Levesque is licensed under a Creative Commons Attribution 4.0 International License, except where otherwise noted.