Statistics for chemical and process engineers : a modern approach / Yuri A.W. Shardt.
2022
TP165 .S53 2022
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Online Access
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Unlimited
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Can lend chapters, not whole ebooks
Details
Title
Statistics for chemical and process engineers : a modern approach / Yuri A.W. Shardt.
Author
Shardt, Yuri A. W., author.
Edition
Second edition.
ISBN
9783030831905 (electronic bk.)
3030831906 (electronic bk.)
9783030831899
3030831892
3030831906 (electronic bk.)
9783030831899
3030831892
Published
Cham : Springer, [2022]
Copyright
©2022
Language
English
Description
1 online resource : illustrations (some color)
Other Standard Identifiers
10.1007/978-3-030-83190-5 doi
Call Number
TP165 .S53 2022
Dewey Decimal Classification
660.01/5195
Summary
A coherent, concise, and comprehensive course in the statistics needed for a modern career in chemical engineering covers all of the concepts required for the American Fundamentals of Engineering Examination. Statistics for Chemical and Process Engineers (second edition) shows the reader how to develop and test models, design experiments and analyze data in ways easily applicable through readily available software tools like MS Excel and MATLAB and is updated for the most recent versions of both. Generalized methods that can be applied irrespective of the tool at hand are a key feature of the text, and it now contains an introduction to the use of state-space methods. The reader is given a detailed framework for statistical procedures covering: data visualization; probability; linear and nonlinear regression; experimental design (including factorial and fractional factorial designs); and dynamic process identification. Main concepts are illustrated with chemical- and process-engineering-relevant examples that can also serve as the bases for checking any subsequent real implementations. Questions are provided (with solutions available for instructors) to confirm the correct use of numerical techniques, and templates for use in MS Excel and MATLAB are also available for download. With its integrative approach to system identification, regression, and statistical theory, this book provides an excellent means of revision and self-study for chemical and process engineers working in experimental analysis and design in petrochemicals, ceramics, oil and gas, automotive and similar industries, and invaluable instruction to advanced undergraduate and graduate students looking to begin a career in the process industries.
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Digital File Characteristics
text file PDF
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed January 12, 2022).
Available in Other Form
Print version: 9783030831899
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Online Access
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Table of Contents
Introduction to Statistics and Data Visualisation
Theoretical Foundation for Statistical Analysis
Regression
Design of Experiments
Modelling Stochastic Processes with Time Series Analysis
Modelling Dynamic Processes Using System Identification Methods
Using MATLAB for Statistical Analysis
Using Excel to do Statistical Analysis.
Theoretical Foundation for Statistical Analysis
Regression
Design of Experiments
Modelling Stochastic Processes with Time Series Analysis
Modelling Dynamic Processes Using System Identification Methods
Using MATLAB for Statistical Analysis
Using Excel to do Statistical Analysis.