Statistics for chemical engineers : from data to models to decisions /
Build a firm foundation for studying statistical modelling, data science and machine learning with this practical introduction to statistics, written with chemical engineers in mind. It introduces a data–model–decision approach to applying statistical methods to real-world chemical engineering chall...
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| Format: | Book |
| Language: | English |
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Cambridge ; New York :
Cambridge University Press,
2025.
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| Series: | Cambridge series in chemical engineering.
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| Summary: | Build a firm foundation for studying statistical modelling, data science and machine learning with this practical introduction to statistics, written with chemical engineers in mind. It introduces a data–model–decision approach to applying statistical methods to real-world chemical engineering challenges, establishes links between statistics, probability, linear algebra, calculus and optimization, and covers classical and modern topics such as uncertainty quantification, risk modelling and decision-making under uncertainty. Over 100 worked examples using Matlab and Python demonstrate how to apply theory to practice, with over 70 end-of-chapter problems to reinforce student learning, and key topics are introduced using a modular structure, which supports learning at a range of paces and levels. Requiring only a basic understanding of calculus and linear algebra, this textbook is the ideal introduction for undergraduate students in chemical engineering, and a valuable preparatory text for advanced courses in data science and machine learning with chemical engineering applications. |
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| Physical Description: | xxii, 444 pages : illustrations ; 26 cm. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9781009541893 1009541897 |