Statistics for Chemical Engineers
From Data to Models to Decisions
Seiten
2025
Cambridge University Press (Verlag)
978-1-009-54189-3 (ISBN)
Cambridge University Press (Verlag)
978-1-009-54189-3 (ISBN)
This practical introduction to statistics written with chemical engineers in mind, emphasizes real-world problem solving. Including over 100 Matlab and Python examples, accompanied by lecture slides, code and solutions for instructors, it is ideal for chemical engineering students keen to advance to courses in data science and machine learning.
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.
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.
Victor M. Zavala is the Baldovin-DaPra Professor of Chemical and Biological Engineering at the University of Wisconsin, Madison and a Senior Computational Mathematician at Argonne National Laboratory. He is the recipient of the Harvey Spangler Award for Innovative Teaching and Learning Practices from the College of Engineering at UW-Madison, and of the Presidential Early Career Award for Scientists and Engineers (PECASE).
1. Introduction to statistics; 2. Univariate random variables; 3. Multivariate random variables; 4. Estimation for random variables; 5. Estimation for structural models; 6. Statistical learning; 7. Decision-making under uncertainty.
| Erscheinungsdatum | 16.09.2025 |
|---|---|
| Reihe/Serie | Cambridge Series in Chemical Engineering |
| Zusatzinfo | Worked examples or Exercises |
| Verlagsort | Cambridge |
| Sprache | englisch |
| Themenwelt | Naturwissenschaften ► Chemie ► Technische Chemie |
| Technik ► Umwelttechnik / Biotechnologie | |
| ISBN-10 | 1-009-54189-7 / 1009541897 |
| ISBN-13 | 978-1-009-54189-3 / 9781009541893 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
| Haben Sie eine Frage zum Produkt? |
Mehr entdecken
aus dem Bereich
aus dem Bereich
Daten, Formeln, Normen, vergleichende Betrachtungen
Buch | Softcover (2024)
Europa-Lehrmittel (Verlag)
CHF 56,90
Von der Theorie zur Anwendung
Buch | Hardcover (2025)
Hanser (Verlag)
CHF 55,95
