Description
Statistics for Chemical and Process Engineers, Softcover reprint of the original 1st ed. 2015
A Modern Approach
Language: EnglishSubjects for Statistics for Chemical and Process Engineers:
Keywords
ANOVA Analysis; Data Mining Chemistry; Data Visualization; Design of Experiments; FE Review Manual; Fundamentals of Engineering Exam Review Book; Generalised Factorial Design; Interpretation of Experiments; Introductory Statistics; Principal Component Analysis; Regression Analysis; System Identification
Support: Print on demand
Description
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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.
This book shows the reader how to develop and test models, design experiments and analyse data in ways easily applicable through readily available software tools like MS Excel® and MATLAB®. Generalized methods that can be applied irrespective of the tool at hand are a key feature of the text.
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 can also be downloaded from extras.springer.com.
With its integrative approach to system identification, regression and statistical theory, Statistics for Chemical and Process Engineers 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.
1. Introduction to Statistics and Data Visualisation.- 2. Theoretical Foundation for Statistical Analysis.- 3. Regression.- 4. Design of Experiments.- 5. Modelling Stochastic Processes with Time Series Analysis.- 6. Modelling Dynamic Processes Using System Identification Methods.- 7.- Using MATLAB® for Statistical Analysis.- 8 : Using Excel® to do Statistical Analysis.
Covers all concepts required by the American Fundamentals of Engineering Examination
Helps the reader perform correct data analysis by providing detailed guidance frameworks in addition to the conceptual presentation
Emphasizes examples relevant to chemical and process engineers especially those new to statistical analysis
Microsoft Excel Templates facilitate the use of the methods presented without requiring the practitioner to have access to specialized software
Generalized exposition of results means they can be put to use in the widest range of applications possible
Integrative approach to system identification, linear regression and statistical theory helps the reader to understand the similarities and differences in the methods used
Includes supplementary material: sn.pub/extras