Statistics A Concise Mathematical Introduction for Students, Scientists, and Engineers

“Statistics: A Concise Mathematical Introduction for Students, Scientists, and Engineers” by David W. Scott is published by John Wiley & Sons on July 13, 2020, and spans 180 pages. This book serves as a comprehensive academic resource designed to enhance students’ skills in statistics, probability, and inference, preparing them for advanced courses in various fields such as engineering, computer science, and data sciences.
Readers will find a focus on both continuous measurements and discrete random variables, utilizing intuitive models and geometric probability throughout the text. The book covers classical probability, random variables, and inference, along with special topics relevant to understanding data. It is particularly suited for undergraduates in science and engineering disciplines, and includes supplementary resources such as sample R and Mathematica code available on an accompanying website, making it a practical tool for both instructors and students.
Official synopsis Publisher
Statistic: A Concise Mathematical Introduction for Students and Scientists offers a one academic term text that prepares the student to broaden their skills in statistics, probability and inference, prior to selecting their follow-on courses in their chosen fields, whether it be engineering, computer science, programming, data sciences, business or economics.
The book places focus early on continuous measurements, as well as discrete random variables. By invoking simple and intuitive models and geometric probability, discrete and continuous experiments and probabilities are discussed throughout the book in a natural way. Classical probability, random variables, and inference are discussed, as well as material on understanding data and topics of special interest.
Topics discussed include:
• Classical equally likely outcomes
• Variety of models of discrete and continuous probability laws
• Likelihood function and ratio
• Inference
• Bayesian statistics
With the growth in the volume of data generated in many disciplines that is enabling the growth in data science, companies now demand statistically literate scientists and this textbook is the answer, suited for undergraduates studying science or engineering, be it computer science, economics, life sciences, environmental, business, amongst many others. Basic knowledge of bivariate calculus, R language, Matematica and JMP is useful, however there is an accompanying website including sample R and Mathematica code to help instructors and students.
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