Statistics for Chemical and Process Engineers

A Modern Approach

  • Yuri A.W. Shardt

Table of contents

  1. Front Matter
    Pages i-xxvi
  2. Yuri A. W. Shardt
    Pages 31-85
  3. Yuri A. W. Shardt
    Pages 87-140
  4. Yuri A. W. Shardt
    Pages 141-209
  5. Yuri A. W. Shardt
    Pages 337-362
  6. Yuri A. W. Shardt
    Pages 363-398
  7. Back Matter
    Pages 399-414

About this book


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

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.



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

Authors and affiliations

  • Yuri A.W. Shardt
    • 1
  1. 1.Institute of Automation and Complex Systems (AKS)University of Duisburg-EssenDuisbergGermany

Bibliographic information

Industry Sectors
Chemical Manufacturing
Consumer Packaged Goods
Oil, Gas & Geosciences