8 Best Books on Process Data Analysis and Design of Experiments

We have compiled a list of the Best Reference Books on Process Data Analysis and Design of Experiments, which are used by students of top universities, and colleges. This will help you choose the right book depending on if you are a beginner or an expert. Here is the complete list of Process Data Analysis and Design of Experiments Books with their authors, publishers, and an unbiased review of them as well as links to the Amazon website to directly purchase them. If permissible, you can also download the free PDF books on Process Data Analysis and Design of Experiments below.

1."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.
2."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.
3."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.
4."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.
5."Linear Estimation and Design Of Experiments" by D Joshi “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.
6."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. advertisement advertisement
7."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.
8."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.

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