Mathematics for Engineers and Scientists: Concepts, Applications, and History

By Vinh Phu Nguyen

A majority of mathematics textbooks are written in a rigorous, concise, dry, and boring way. On the other hands, there exist excellent, engaging, fun-to-read popular math books. The problem with these popular books is the lack of mathematics itself. This book is a blend of both. It provides a mathematics book to read, to engage with, and to understand the whys -- the story behind the theorems. Written by an engineer, not a mathematician, who struggled to learn math in high school and in university, this book explains in an informal voice the mathematics that future and current engineering and science students need to acquire. If we learn math to understand it, to enjoy it, not to pass a test or an exam, we all learn math better and there is no such a thing that we call math phobia. With a slow pace and this book, everyone can learn math and use it, as the author did at the age of 40 and with a family to take care of.

• Format: Hardcover
• Language: English
• ISBN: 9819746302
• ISBN13: 9789819746309
• Release Date: January 2025
• Publisher: Springer
• Length: 1093 Pages

Customer Reviews

a practical reference

Experimental design analyzing with linear models has been on the notation for decades. The book, although somewhat antique, is still an envaluable reference.

Best Book Out There

I have used this book when it was in its first edition and only by Neter and Wasserman. An absolute must for those who use linear models (regression and ANOVA) and want the most exhaustive book out there. This book is one of the rare texts that is also extremely well written. You can not go wrong reading it and studying it on your own. If you can take only one statistics book with you, this is the one. I use the 4th edition...

A great book for a course, for reference, and to keep!

This book seems very difficult and long to read at first, but as soon as I got into the habit of using this book, this is really a great book to have. The terminologies are very easy to understand and yet not redundant, and it has some great reference areas in the sections that you could look up for information when you need to work on an exercise or a project. The exercises in the back of each section are ample enough so...

A fine job

The linear model lies at the heart of a wide variety of familiar statistical methods, including regression, anova, and ancova. Anyone with a professional interest in statistics must get to know it well. This book is a clear, well organized, and practical presentation of the linear model. It is not pie-in-the-sky or esoteric. It leads the reader carefully through the real world problems that are encountered in applying...

must buy, especially for students

I definitely recommend this book to anyone who wishes to understand how to implement the linear model. This book shows the theory and then gives comprehensive examples explaining when and how to apply the theory. The book made few assumptions about readers having a certain level of specialized knowledge, such as familiarity with matrix math. The math presented in the book is thoroughly explained from the ground up using...