Experimental Design Techniques In Statistical Practice
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Experimental Design Techniques in Statistical Practice by William P Gardiner,G Gettinby Pdf
Provides an introduction to the diverse subject area of experimental design, with many practical and applicable exercises to help the reader understand, present and analyse the data. The pragmatic approach offers technical training for use of designs and teaches statistical and non-statistical skills in design and analysis of project studies throughout science and industry. Provides an introduction to the diverse subject area of experimental design and includes practical and applicable exercises to help understand, present and analyse the data Offers technical training for use of designs and teaches statistical and non-statistical skills in design and analysis of project studies throughout science and industry Discusses one-factor designs and blocking designs, factorial experimental designs, Taguchi methods and response surface methods, among other topics
Understanding Statistics and Experimental Design by Michael H. Herzog,Gregory Francis,Aaron Clarke Pdf
This open access textbook provides the background needed to correctly use, interpret and understand statistics and statistical data in diverse settings. Part I makes key concepts in statistics readily clear. Parts I and II give an overview of the most common tests (t-test, ANOVA, correlations) and work out their statistical principles. Part III provides insight into meta-statistics (statistics of statistics) and demonstrates why experiments often do not replicate. Finally, the textbook shows how complex statistics can be avoided by using clever experimental design. Both non-scientists and students in Biology, Biomedicine and Engineering will benefit from the book by learning the statistical basis of scientific claims and by discovering ways to evaluate the quality of scientific reports in academic journals and news outlets.
Statistics and Experimental Design for Psychologists by Rory Allen Pdf
This is the first textbook for psychologists which combines the model comparison method in statistics with a hands-on guide to computer-based analysis and clear explanations of the links between models, hypotheses and experimental designs. Statistics is often seen as a set of cookbook recipes which must be learned by heart. Model comparison, by contrast, provides a mental roadmap that not only gives a deeper level of understanding, but can be used as a general procedure to tackle those problems which can be solved using orthodox statistical methods. Statistics and Experimental Design for Psychologists focusses on the role of Occam's principle, and explains significance testing as a means by which the null and experimental hypotheses are compared using the twin criteria of parsimony and accuracy. This approach is backed up with a strong visual element, including for the first time a clear illustration of what the F-ratio actually does, and why it is so ubiquitous in statistical testing. The book covers the main statistical methods up to multifactorial and repeated measures, ANOVA and the basic experimental designs associated with them. The associated online supplementary material extends this coverage to multiple regression, exploratory factor analysis, power calculations and other more advanced topics, and provides screencasts demonstrating the use of programs on a standard statistical package, SPSS. Of particular value to third year undergraduate as well as graduate students, this book will also have a broad appeal to anyone wanting a deeper understanding of the scientific method. Contents: What is Science?Comparing Different Models of a Set of DataTesting Hypotheses and Recording the Result: Types of ValidityBasic Descriptive Statistics (and How Pierre Laplace Saved the World)Bacon's Legacy: Causal Models, and How to Test ThemHow Hypothesis Testing Copes with Uncertainty: The Legacy of Karl Popper and Ronald FisherGaussian Distributions, the Building Block of Parametric StatisticsRandomized Controlled Trials, the Model T Ford of ExperimentsThe Independent Samples t-Test, the Analytical Engine of the RCTGeneralising the t-Test: One-Way ANOVAMultifactorial Designs and Their ANOVA CounterpartsRepeated Measures Designs, and Their ANOVA CounterpartsAppendices:On Finding the Right Effect SizeWhy Orthogonal Contrasts are UsefulMathematical Justification for the Occam LineGlossaryFurther ReadingReferencesIndex Readership: Students of undergraduate and graduate level psychology, and academics involved in research.
Design and Analysis of Experiments, Volume 1 by Klaus Hinkelmann,Oscar Kempthorne Pdf
This user-friendly new edition reflects a modern and accessible approach to experimental design and analysis Design and Analysis of Experiments, Volume 1, Second Edition provides a general introduction to the philosophy, theory, and practice of designing scientific comparative experiments and also details the intricacies that are often encountered throughout the design and analysis processes. With the addition of extensive numerical examples and expanded treatment of key concepts, this book further addresses the needs of practitioners and successfully provides a solid understanding of the relationship between the quality of experimental design and the validity of conclusions. This Second Edition continues to provide the theoretical basis of the principles of experimental design in conjunction with the statistical framework within which to apply the fundamental concepts. The difference between experimental studies and observational studies is addressed, along with a discussion of the various components of experimental design: the error-control design, the treatment design, and the observation design. A series of error-control designs are presented based on fundamental design principles, such as randomization, local control (blocking), the Latin square principle, the split-unit principle, and the notion of factorial treatment structure. This book also emphasizes the practical aspects of designing and analyzing experiments and features: Increased coverage of the practical aspects of designing and analyzing experiments, complete with the steps needed to plan and construct an experiment A case study that explores the various types of interaction between both treatment and blocking factors, and numerical and graphical techniques are provided to analyze and interpret these interactions Discussion of the important distinctions between two types of blocking factors and their role in the process of drawing statistical inferences from an experiment A new chapter devoted entirely to repeated measures, highlighting its relationship to split-plot and split-block designs Numerical examples using SAS® to illustrate the analyses of data from various designs and to construct factorial designs that relate the results to the theoretical derivations Design and Analysis of Experiments, Volume 1, Second Edition is an ideal textbook for first-year graduate courses in experimental design and also serves as a practical, hands-on reference for statisticians and researchers across a wide array of subject areas, including biological sciences, engineering, medicine, pharmacology, psychology, and business.
Data Analysis for Experimental Design by Richard Gonzalez Pdf
This engaging text shows how statistics and methods work together, demonstrating a variety of techniques for evaluating statistical results against the specifics of the methodological design. Richard Gonzalez elucidates the fundamental concepts involved in analysis of variance (ANOVA), focusing on single degree-of-freedom tests, or comparisons, wherever possible. Potential threats to making a causal inference from an experimental design are highlighted. With an emphasis on basic between-subjects and within-subjects designs, Gonzalez resists presenting the countless "exceptions to the rule" that make many statistics textbooks so unwieldy and confusing for students and beginning researchers. Ideal for graduate courses in experimental design or data analysis, the text may also be used by advanced undergraduates preparing to do senior theses. Useful pedagogical features include: Discussions of the assumptions that underlie each statistical test Sequential, step-by-step presentations of statistical procedures End-of-chapter questions and exercises Accessible writing style with scenarios and examples This book is intended for graduate students in psychology and education, practicing researchers seeking a readable refresher on analysis of experimental designs, and advanced undergraduates preparing senior theses. It serves as a text for graduate level experimental design, data analysis, and experimental methods courses taught in departments of psychology and education. It is also useful as a supplemental text for advanced undergraduate honors courses.
Experiment Design and Statistical Methods For Behavioural and Social Research by David R. Boniface Pdf
Experiment Design and Statistical Methods introduces the concepts, principles, and techniques for carrying out a practical research project either in real world settings or laboratories - relevant to studies in psychology, education, life sciences, social sciences, medicine, and occupational and management research. The text covers: repeated measures unbalanced and non-randomized experiments and surveys choice of design adjustment for confounding variables model building and partition of variance covariance multiple regression Experiment Design and Statistical Methods contains a unique extension of the Venn diagram for understanding non-orthogonal design, and it includes exercises for developing the reader's confidence and competence. The book also examines advanced techniques for users of computer packages or data analysis, such as Minitab, SPSS, SAS, SuperANOVA, Statistica, BMPD, SYSTAT, Genstat, and GLIM.
Experimental and Quasi-Experimental Designs for Research by Donald T. Campbell,Julian C. Stanley Pdf
We shall examine the validity of 16 experimental designs against 12 common threats to valid inference. By experiment we refer to that portion of research in which variables are manipulated and their effects upon other variables observed. It is well to distinguish the particular role of this chapter. It is not a chapter on experimental design in the Fisher (1925, 1935) tradition, in which an experimenter having complete mastery can schedule treatments and measurements for optimal statistical efficiency, with complexity of design emerging only from that goal of efficiency. Insofar as the designs discussed in the present chapter become complex, it is because of the intransigency of the environment: because, that is, of the experimenter’s lack of complete control.
Practical Guide to Experimental Design by Normand L. Frigon,David Mathews Pdf
Over the last decade, Design of Experiments (DOE) has become established as a prime analytical and forecasting method with a vital role to play in product and process improvement. Now Practical Guide to Experimental Design lets you put this high-level statistical technique to work in your field, whether you are in the manufacturing or services sector. This accessible book equips you with all of the basic technical and managerial skills you need to develop, execute, and evaluate designed experiments effectively. You will develop a solid grounding in the statistical underpinnings of DOE, including distributions, analysis of variance, and more. You will also gain a firm grasp of full and fractional factorial techniques, the use of DOE in fault isolation and failure analysis, and the application of individual DOE methods within an integrated system. Each procedure is clearly illustrated one step at a time with the help of simplified notation and easy-to-understand spreadsheets. The book's real-world approach is reinforced throughout by case studies, examples, and exercises taken from a broad cross section of business applications. Practical Guide to Experimental Design is a valuable competitive asset for engineers, scientists, and decision-makers in many industries, as well as an important resource for researchers and advanced students. This hands-on guide offers complete, down-to-earth coverage of Design of Experiments (DOE) basics, providing you with the technical and managerial tools you need to put this powerful technique into action to help you achieve your quality improvement objectives. Using a clear, step-by-step approach, Practical Guide to Experimental Design shows you how to develop, perform, and analyze designed experiments. The book features: * Accessible coverage of statistical concepts, including data acquisition, reporting of results, sampling and other distributions, and more * A complete range of analytical procedures - analysis of variance, full and fractional factorial DOE, and the role of DOE in fault isolation and failure analysis * In-depth case studies, examples, and exercises covering a range of different uses of DOE * Broad applications across manufacturing, service, administrative, and other business sectors No matter what your field, Practical Guide to Experimental Design provides you with the "on-the-ground" assistance necessary to transform DOE theory into practice - the ideal guide for engineers, scientists, researchers, and advanced students.
Statistical Methods, Experimental Design, and Scientific Inference by R. A. Fisher Pdf
The writings of R.A. Fisher have proved to be as relevant today as when they were written. This book brings together as a single volume three of his most influential textbooks: Statistical Methods for Research Workers, Statistical Methods and Scientific Inference, and The Design of Experiments. In a new Foreword, written for this edition, Professor Frank Yates discusses some of the key issues tackled in the textbooks, and how they relate to modern statistical practice.
Statistical Practice in Business and Industry by Shirley Coleman,Tony Greenfield,Dave Stewardson,Douglas C. Montgomery Pdf
This book covers all the latest advances, as well as more established methods, in the application of statistical and optimisation methods within modern industry. These include applications from a range of industries that include micro-electronics, chemical, automotive, engineering, food, component assembly, household goods and plastics. Methods range from basic graphical approaches to generalised modelling, from designed experiments to process control. Solutions cover produce and process design, through manufacture to packaging and delivery, from single responses to multivariate problems.
Optimal Design of Experiments by Peter Goos,Bradley Jones Pdf
"This is an engaging and informative book on the modern practice of experimental design. The authors' writing style is entertaining, the consulting dialogs are extremely enjoyable, and the technical material is presented brilliantly but not overwhelmingly. The book is a joy to read. Everyone who practices or teaches DOE should read this book." - Douglas C. Montgomery, Regents Professor, Department of Industrial Engineering, Arizona State University "It's been said: 'Design for the experiment, don't experiment for the design.' This book ably demonstrates this notion by showing how tailor-made, optimal designs can be effectively employed to meet a client's actual needs. It should be required reading for anyone interested in using the design of experiments in industrial settings." —Christopher J. Nachtsheim, Frank A Donaldson Chair in Operations Management, Carlson School of Management, University of Minnesota This book demonstrates the utility of the computer-aided optimal design approach using real industrial examples. These examples address questions such as the following: How can I do screening inexpensively if I have dozens of factors to investigate? What can I do if I have day-to-day variability and I can only perform 3 runs a day? How can I do RSM cost effectively if I have categorical factors? How can I design and analyze experiments when there is a factor that can only be changed a few times over the study? How can I include both ingredients in a mixture and processing factors in the same study? How can I design an experiment if there are many factor combinations that are impossible to run? How can I make sure that a time trend due to warming up of equipment does not affect the conclusions from a study? How can I take into account batch information in when designing experiments involving multiple batches? How can I add runs to a botched experiment to resolve ambiguities? While answering these questions the book also shows how to evaluate and compare designs. This allows researchers to make sensible trade-offs between the cost of experimentation and the amount of information they obtain.
Experimental Design Research by Philip Cash,Tino Stanković,Mario Štorga Pdf
This book presents a new, multidisciplinary perspective on and paradigm for integrative experimental design research. It addresses various perspectives on methods, analysis and overall research approach, and how they can be synthesized to advance understanding of design. It explores the foundations of experimental approaches and their utility in this domain, and brings together analytical approaches to promote an integrated understanding. The book also investigates where these approaches lead to and how they link design research more fully with other disciplines (e.g. psychology, cognition, sociology, computer science, management). Above all, the book emphasizes the integrative nature of design research in terms of the methods, theories, and units of study—from the individual to the organizational level. Although this approach offers many advantages, it has inherently led to a situation in current research practice where methods are diverging and integration between individual, team and organizational understanding is becoming increasingly tenuous, calling for a multidisciplinary and transdiscipinary perspective. Experimental design research thus offers a powerful tool and platform for resolving these challenges. Providing an invaluable resource for the design research community, this book paves the way for the next generation of researchers in the field by bridging methods and methodology. As such, it will especially benefit postgraduate students and researchers in design research, as well as engineering designers.
Design and Analysis of Experiments, Volume 3 by Klaus Hinkelmann Pdf
Provides timely applications, modifications, and extensions of experimental designs for a variety of disciplines Design and Analysis of Experiments, Volume 3: Special Designs and Applications continues building upon the philosophical foundations of experimental design by providing important, modern applications of experimental design to the many fields that utilize them. The book also presents optimal and efficient designs for practice and covers key topics in current statistical research. Featuring contributions from leading researchers and academics, the book demonstrates how the presented concepts are used across various fields from genetics and medicinal and pharmaceutical research to manufacturing, engineering, and national security. Each chapter includes an introduction followed by the historical background as well as in-depth procedures that aid in the construction and analysis of the discussed designs. Topical coverage includes: Genetic cross experiments, microarray experiments, and variety trials Clinical trials, group-sequential designs, and adaptive designs Fractional factorial and search, choice, and optimal designs for generalized linear models Computer experiments with applications to homeland security Robust parameter designs and split-plot type response surface designs Analysis of directional data experiments Throughout the book, illustrative and numerical examples utilize SAS®, JMP®, and R software programs to demonstrate the discussed techniques. Related data sets and software applications are available on the book's related FTP site. Design and Analysis of Experiments, Volume 3 is an ideal textbook for graduate courses in experimental design and also serves as a practical, hands-on reference for statisticians and researchers across a wide array of subject areas, including biological sciences, engineering, medicine, and business.
Statistical Analysis of Designed Experiments by Helge Toutenburg,Shalabh Pdf
Unique in commencing with relatively simple statistical concepts and ideas found in most introductory statistical textbooks, this book goes on to cover more material useful for undergraduates and graduate in statistics and biostatistics.
Statistical Design and Analysis of Experiments by Robert L. Mason,Richard F. Gunst,James L. Hess Pdf
Emphasizes the strategy of experimentation, data analysis, and the interpretation of experimental results. Features numerous examples using actual engineering and scientific studies. Presents statistics as an integral component of experimentation from the planning stage to the presentation of the conclusions. Deep and concentrated experimental design coverage, with equivalent but separate emphasis on the analysis of data from the various designs. Topics can be implemented by practitioners and do not require a high level of training in statistics. New edition includes new and updated material and computer output.