Best Reference Books – Process Data Analysis and Design of Experiments

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We have compiled a list of Best Reference Books on Process Data Analysis and Design of Experiments Subject. These books are used by students of top universities, institutes and colleges.

Here is the full list of best reference books on Process Data Analysis and Design of Experiments.

We have put a lot of effort into researching the best books for reference on this subject and came out with a recommended list of best books. The table below contains a review of these books and links to the Amazon website to directly purchase these books. As an Amazon Associate, we earn from qualifying purchases, but this does not impact our reviews, comparisons, and listing of these books; the table serves as a ready reckoner list of these best books.

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1. “Applied Statistics and Probability for Engineers” by Douglas C Montgomery and G C Runger

Book Review: This book presents a practical approach to chemical sciences, physical sciences and engineering. This is very good textbook for courses in probability and statistics. The book stresses on real engineering applications and real engineering solutions and also includes material on bootstrap, P value usage, equivalence testing, p values combination and contains numerous examples on the same.

2. “Introduction to Linear Regression Analysis” by Douglas C Montgomery and G G Vining

Book Review: This book provides introduction to the basics of regression analysis. The book presents both theoretical concepts and applications thereby helping the readers to understand the principles that are needed to apply for regression model building techniques in different streams like engineering, management and health sciences. The book includes a discussion on transformations and weighted least squares that are used to resolve problems of model inadequacy and influential observations. This is a very good book for statistics and engineering courses on regression at the graduate and undergraduate levels.

3. “Applied Regression Analysis” by Norman R Draper and Harry Smith

Book Review: This book gives very good introduction to the basics of regression analysis. The book also discusses the statistical tools that are used for establishing relationships between variables. The book also stresses on the presentation of concepts and applications and provides solid introduction to the fundamentals of regression analysis. The book also checks both linear and non-linear regression models and contains chapters on generalized linear models, regression geometry, robust regression and resampling procedures. This book is useful for analysts, researchers and university students for courses on regression.

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4. “Statistics for Experimenters: An Introduction to Design, Data Analysis and Model Building” by George E P Box and J S Hunter

Book Review: The various topics covered in the book are innovation catalysis, problem solving and discovery. The book also describes scientific experimentation and the tools needed to increase the knowledge gained from research data. The book explains the usage of these tools during all the stages of investigation process. The author first describes the problem that has to be solved and later examines the statistical methods of design and analysis. The topics in the book are variance graphical analysis, complex design computer analysis, transformation simplification, process control basics and many more.

5. “Computational Complexity and Feasibility of Data Processing and Interval Computations” by Vladik Kreinovich

“Computational Complexity and Feasibility of Data Processing and Interval Computations” Book Review: The book mainly presents ideas on data processing. Numerical computations experts, students of applied mathematics can access the book. The book describes numerical optimization and algorithms for automatic verification. Computational complexity of numerical numerical computations is covered. The book also lists general techniques employed for estimation of computational complexity. The book presents many real life examples for better understanding and implementation of the concepts.

6. “Applied Design of Experiments And Taguchi Methods” by P Shahabudeen and K Krishnaiah

“Applied Design of Experiments And Taguchi Methods” Book Review: The book covers the fundamentals of experimental design concepts. It targets students of undergraduate or postgraduate level courses in the field. It covers key topics such as DOE techniques for process improvement, and simple graphical methods for reducing the time taken to design and develop products. Statistical model for two-factor three-factor experiments, 2k and 2k-m factorial design is explained. Concepts of methodology of surface design, Taguchi quality loss function, orthogonal design, and objective functions in robust design, are also entailed. A few other concepts inculcated are: application of orthogonal arrays, data analysis using response graph method and analysis of variance, methods for multi-level factor designs, factor analysis and genetic algorithm.

7. “Linear Estimation and Design Of Experiments” by D Joshi

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“Linear Estimation and Design Of Experiments” Book Review: The main idea of the book is mathematical theory for experimental design. The book is recommended to students fresh to the field. Emphasis is laid on the application of general mathematical theory of linear theory of least squares used in the analysis of fixed-effects linear model experimental design. The book also covers mathematical theory, its applications to design and computational techniques.

8. “Design of Experiments” by Virgil L Anderson

“Design of Experiments” Book Review: The book describes basic aspects of designing experiments. It can be accessed by researchers or students interested in experimental design. The book initially explains the mathematical concepts required for the subject in the first two chapters. The next few chapters focus on design of experiments and their relevance in scientific methods. The book also covers the standard problems faced by experimental designs and methods for efficient analysis of results of various experimental methods. The reader can find numerous problems at the end of each chapter for a better understanding of the concepts.

9. “Design of a reliable processing system for satellite data” by Francesco Lazzarotto

“Design of a reliable processing system for satellite data” Book Review: The focus of the book is on design of a data handling space system based on events triggering. The book covers key areas such as reliability of software and hardware paradigms. A real application to describe methods and models and the software produced oriented towards problem solving is used in the book. Concepts of dimensioned control and reconfiguration systems for reducing failure and maintaining the working state are also covered. A few other concepts explained are: environmental stress component, efficiency, functionality of space systems.

10. “Introduction to Orthogonal Transforms: With Applications in Data Processing and Analysis” by Ruye Wang

“Introduction to Orthogonal Transforms: With Applications in Data Processing and Analysis” Book Review: The book deals with orthogonal transform methods for signal processing, data analysis and communications. Practitioners and students alike can access this book. Each method is described in detail covering signal decorrelation and energy compaction parameters. The methods covered in the book are Fourier, Laplace, Z-, Walsh-Hadamard, Slant, Haar, Karhunen-Loève and wavelet transforms. Application and implementation of each method is elucidated. The concepts of the book are strengthened by problems at the end of each chapter. The book is also aided by online Matlab and C code and an instructor-only solutions manual.

People who are searching for Free downloads of books and free pdf copies of these books – “Applied Statistics and Probability for Engineers” by Douglas C Montgomery and G C Runger, “Introduction to Linear Regression Analysis” by Douglas C Montgomery and G G Vining, “Applied Regression Analysis” by Norman R Draper and Harry Smith, “Statistics for Experimenters: An Introduction to Design, Data Analysis and Model Building” by George E P Box and J S Hunter, “Computational Complexity and Feasibility of Data Processing and Interval Computations” by Vladik Kreinovich, “Applied Design Of Experiments And Taguchi Methods” by P Shahabudeen and K Krishnaiah, “Linear Estimation And Design Of Experiments” by D Joshi, “Design of Experiments” by Virgil L Anderson, “Design of a reliable processing system for satellite data” by Francesco Lazzarotto, “Introduction to Orthogonal Transforms: With Applications in Data Processing and Analysis” by Ruye Wang – we would like to mention that we don’t have free downloadable pdf copies of these good books and one should look for free pdf copies from these Authors only if they have explicitly made it free to download and read them.

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We have created a collection of best reference books on “Process Data Analysis and Design of Experiments” so that one can readily see the list of top books on “Process Data Analysis and Design of Experiments” and buy the books either online or offline.

If any more book needs to be added to the list of best books on Process Data Analysis and Design of Experiments Subject, please let us know.

Sanfoundry Global Education & Learning Series – Best Reference Books!

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Manish Bhojasia, a technology veteran with 20+ years @ Cisco & Wipro, is Founder and CTO at Sanfoundry. He is Linux Kernel Developer & SAN Architect and is passionate about competency developments in these areas. He lives in Bangalore and delivers focused training sessions to IT professionals in Linux Kernel, Linux Debugging, Linux Device Drivers, Linux Networking, Linux Storage, Advanced C Programming, SAN Storage Technologies, SCSI Internals & Storage Protocols such as iSCSI & Fiber Channel. Stay connected with him @ LinkedIn