Download or read book Comparison of Statistical Experiments written by Erik Torgersen and published by Cambridge University Press. This book was released on 1991-03-14 with total page 706 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are a number of important questions associated with statistical experiments: when does one given experiment yield more information than another; how can we measure the difference in information; how fast does information accumulate by repeating the experiment? The means of answering such questions has emerged from the work of Wald, Blackwell, LeCam and others and is based on the ideas of risk and deficiency. The present work which is devoted to the various methods of comparing statistical experiments, is essentially self-contained, requiring only some background in measure theory and functional analysis. Chapters introducing statistical experiments and the necessary convex analysis begin the book and are followed by others on game theory, decision theory and vector lattices. The notion of deficiency, which measures the difference in information between two experiments, is then introduced. The relation between it and other concepts, such as sufficiency, randomisation, distance, ordering, equivalence, completeness and convergence are explored. This is a comprehensive treatment of the subject and will be an essential reference for mathematical statisticians.

Download or read book Comparison of Statistical Experiments written by Erik N. Torgersen and published by . This book was released on 2014-05-14 with total page 698 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive treatment of statistical experiments and an essential reference for mathematical statisticians.

Download or read book Statistics and Experimental Design for Psychologists written by Rory Allen and published by World Scientific Publishing Company. This book was released on 2017-08-28 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Designing Experiments and Analyzing Data written by Scott E. Maxwell and published by Routledge. This book was released on 2000 with total page 930 pages. Available in PDF, EPUB and Kindle. Book excerpt: Through this book's unique model comparison approach, students and researchers are introduced to a set of fundamental principles for analyzing data. After seeing how these principles can be applied in simple designs, students are shown how these same principles also apply in more complicated designs. Drs. Maxwell and Delaney believe that the model comparison approach better prepares students to understand the logic behind a general strategy of data analysis appropriate for various designs; and builds a stronger foundation, which allows for the introduction of more complex topics omitted from other books. Several learning tools further strengthen the reader's understanding: *flowcharts assist in choosing the most appropriate technique; *an equation cross-referencing system aids in locating the initial, detailed definition and numerous summary equation tables assist readers in understanding differences between different methods for analyzing their data; *examples based on actual research in a variety of behavioral sciences help students see the applications of the material; *numerous exercises help develop a deeper understanding of the subject. Detailed solutions are provided for some of the exercises and *realistic data sets allow the reader to see an analysis of data from each design in its entirety. Updated throughout, the second edition features: *significantly increased attention to measures of effects, including confidence intervals, strength of association, and effect size estimation for complex and simple designs; *an increased use of statistical packages and the graphical presentation of data; *new chapters (15 & 16) on multilevel models; *the current controversies regarding statistical reasoning, such as the latest debates on hypothesis testing (ch. 2); *a new preview of the experimental designs covered in the book (ch. 2); *a CD with SPSS and SAS data sets for many of the text exercises, as well as tutorials reviewing basic statistics and regression; and *a Web site containing examples of SPSS and SAS syntax for analyzing many of the text exercises. Appropriate for advanced courses on experimental design or analysis, applied statistics, or analysis of variance taught in departments of psychology, education, statistics, business, and other social sciences, the book is also ideal for practicing researchers in these disciplines. A prerequisite of undergraduate statistics is assumed. An Instructor's Solutions Manual is available to those who adopt the book for classroom use.

Download or read book Theory of Statistical Experiments written by H. Heyer and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: By a statistical experiment we mean the procedure of drawing a sample with the intention of making a decision. The sample values are to be regarded as the values of a random variable defined on some meas urable space, and the decisions made are to be functions of this random variable. Although the roots of this notion of statistical experiment extend back nearly two hundred years, the formal treatment, which involves a description of the possible decision procedures and a conscious attempt to control errors, is of much more recent origin. Building upon the work of R. A. Fisher, J. Neyman and E. S. Pearson formalized many deci sion problems associated with the testing of hypotheses. Later A. Wald gave the first completely general formulation of the problem of statisti cal experimentation and the associated decision theory. These achieve ments rested upon the fortunate fact that the foundations of probability had by then been laid bare, for it appears to be necessary that any such quantitative theory of statistics be based upon probability theory. The present state of this theory has benefited greatly from contri butions by D. Blackwell and L. LeCam whose fundamental articles expanded the mathematical theory of statistical experiments into the field of com parison of experiments. This will be the main motivation for the ap proach to the subject taken in this book.

Download or read book The Design of Experiments written by R. Mead and published by Cambridge University Press. This book was released on 1990-07-26 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: In all the experimental sciences, good design of experiments is crucial to the success of research. Well-planned experiments can provide a great deal of information efficiently and can be used to test several hypotheses simultaneously. This book is about the statistical principles of good experimental design and is intended for all applied statisticians and practising scientists engaged in the design, implementation and analysis of experiments. Professor Mead has written the book with the emphasis on the logical principles of statistical design and employs a minimum of mathematics. Throughout he assumes that the large-scale analysis of data will be performed by computers and he is thus able to devote more attention to discussions of how all of the available information can be used to extract the clearest answers to many questions. The principles are illustrated with a wide range of examples drawn from medicine, agriculture, industry and other disciplines. Numerous exercises are given to help the reader practise techniques and to appreciate the difference that good design of experiments can make to a scientific project.

Download or read book Design of Comparative Experiments written by R. A. Bailey and published by Cambridge University Press. This book was released on 2008-04-17 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book should be on the shelf of every practising statistician who designs experiments. Good design considers units and treatments first, and then allocates treatments to units. It does not choose from a menu of named designs. This approach requires a notation for units that does not depend on the treatments applied. Most structure on the set of observational units, or on the set of treatments, can be defined by factors. This book develops a coherent framework for thinking about factors and their relationships, including the use of Hasse diagrams. These are used to elucidate structure, calculate degrees of freedom and allocate treatment subspaces to appropriate strata. Based on a one-term course the author has taught since 1989, the book is ideal for advanced undergraduate and beginning graduate courses. Examples, exercises and discussion questions are drawn from a wide range of real applications: from drug development, to agriculture, to manufacturing.

Download or read book Designing Experiments and Analyzing Data written by Scott E. Maxwell and published by Psychology Press. This book was released on 2004 with total page 1106 pages. Available in PDF, EPUB and Kindle. Book excerpt: CD-ROM contains: "SPSS and SAS data sets fpr ,amu pf tje text exercoses as we;; as titorials reviewing basic statistics and simple and multiple regression."

Download or read book Statistical Analysis of Designed Experiments written by Ajit C. Tamhane and published by John Wiley & Sons. This book was released on 2012-09-12 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt: A indispensable guide to understanding and designing modern experiments The tools and techniques of Design of Experiments (DOE) allow researchers to successfully collect, analyze, and interpret data across a wide array of disciplines. Statistical Analysis of Designed Experiments provides a modern and balanced treatment of DOE methodology with thorough coverage of the underlying theory and standard designs of experiments, guiding the reader through applications to research in various fields such as engineering, medicine, business, and the social sciences. The book supplies a foundation for the subject, beginning with basic concepts of DOE and a review of elementary normal theory statistical methods. Subsequent chapters present a uniform, model-based approach to DOE. Each design is presented in a comprehensive format and is accompanied by a motivating example, discussion of the applicability of the design, and a model for its analysis using statistical methods such as graphical plots, analysis of variance (ANOVA), confidence intervals, and hypothesis tests. Numerous theoretical and applied exercises are provided in each chapter, and answers to selected exercises are included at the end of the book. An appendix features three case studies that illustrate the challenges often encountered in real-world experiments, such as randomization, unbalanced data, and outliers. Minitab® software is used to perform analyses throughout the book, and an accompanying FTP site houses additional exercises and data sets. With its breadth of real-world examples and accessible treatment of both theory and applications, Statistical Analysis of Designed Experiments is a valuable book for experimental design courses at the upper-undergraduate and graduate levels. It is also an indispensable reference for practicing statisticians, engineers, and scientists who would like to further their knowledge of DOE.

Download or read book Experimental Statistics for Agriculture and Horticulture written by Clive R. Ireland and published by CABI. This book was released on 2010 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing practical training supported by a sound theoretical basis, this textbook introduces students to the principles of investigation by experiment and the role of statistics in analysis. It draws on the author's extensive teaching experience and is illustrated with fully worked, contextualized examples throughout, helping readers to correctly design their own experiments and identify the most appropriate technique for analysis. Subjects include sampling and determining sample reliability, hypothesis testing, relationships between variables, the role and use of computer packages such as Microsoft Excel spreadsheet software and GenStat, and more complex experimental designs, such as randomized blocks and split plots. This book is an essential text for students of agriculture, horticulture and related disciplines

Download or read book Experiment Design and Statistical Methods For Behavioural and Social Research written by David R. Boniface and published by Routledge. This book was released on 2019-05-20 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Designing Experiments and Analyzing Data written by Scott E. Maxwell and published by Routledge. This book was released on 2017-09-11 with total page 1056 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designing Experiments and Analyzing Data: A Model Comparison Perspective (3rd edition) offers an integrative conceptual framework for understanding experimental design and data analysis. Maxwell, Delaney, and Kelley first apply fundamental principles to simple experimental designs followed by an application of the same principles to more complicated designs. Their integrative conceptual framework better prepares readers to understand the logic behind a general strategy of data analysis that is appropriate for a wide variety of designs, which allows for the introduction of more complex topics that are generally omitted from other books. Numerous pedagogical features further facilitate understanding: examples of published research demonstrate the applicability of each chapter’s content; flowcharts assist in choosing the most appropriate procedure; end-of-chapter lists of important formulas highlight key ideas and assist readers in locating the initial presentation of equations; useful programming code and tips are provided throughout the book and in associated resources available online, and extensive sets of exercises help develop a deeper understanding of the subject. Detailed solutions for some of the exercises and realistic data sets are included on the website (DesigningExperiments.com). The pedagogical approach used throughout the book enables readers to gain an overview of experimental design, from conceptualization of the research question to analysis of the data. The book and its companion website with web apps, tutorials, and detailed code are ideal for students and researchers seeking the optimal way to design their studies and analyze the resulting data.

Download or read book Statistical Analysis of Designed Experiments written by Helge Toutenburg and published by Springer Science & Business Media. This book was released on 2006-05-09 with total page 507 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Design and Analysis of Experiments for Statistical Selection Screening and Multiple Comparisons written by Robert E. Bechhofer and published by Wiley-Interscience. This book was released on 1995-07-21 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to selection, screening, and multiplecomparisons This book addresses experimenters who have knowledge of classicalexperimental design methodology and expands their repertoire beyondhypothesis testing by providing statistical methods appropriate forselection, screening, and multiple comparisons. It concentrates onthree types of procedures: selection procedures that use the"indifference-zone" approach, screening procedures using the"subset" approach, and multiple comparison procedures involvingnormal means. This is the first book, specifically designed forpractitioners, to bring into focus many developments in the fieldpreviously covered only in university courses. It also presents newresults on the comparison of procedures that have been obtainedspecifically for this volume. This self-contained volume describes methods for designingexperiments when the scientific objective is selection of besttreatments, screening a set of treatments, and multiple comparisonsamong treatment means. The book emphasizes procedures appropriatein a variety of practical settings including those that requireblocking and randomization restriction. It compares the relativemerits of procedures when several different methods can be used inthe same circumstances. Providing practical guidance for experimenters in agriculture,engineering, medicine, and other empirical sciences, this book mayalso be used for a one-semester graduate course in selectionmethodology or to augment traditional courses in experimentaldesign. Design and Analysis of Experiments for Statistical Selection,Screening, and Multiple Comparisons: * Shows how selection and screening can be applied to data thatfollow one of three important probability models--normaldistribution, binomial distribution, and the multinomialdistribution models * Provides an extensive comparison of procedures, allowingexperimenters to choose among competitors when several differentprocedures are feasible for a given application * Gives an extensive set of tables of constants necessary toimplement the procedures * Supplements the tables of constants with listings of FORTRANprograms so that experimenters are not limited to those valuescovered by the tables * Focuses on frequent formulations, while also providing referencesto Bayesian and other alternative developments in the Chapter Notes

Download or read book The Design and Statistical Analysis of Animal Experiments written by Simon T. Bate and published by Cambridge University Press. This book was released on 2014-03-13 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book will provide scientists with a better understanding of statistics, improving their decision-making and reducing animal use.

Download or read book Statistical Principles for the Design of Experiments written by R. Mead and published by Cambridge University Press. This book was released on 2012-09-13 with total page 587 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about the statistical principles behind the design of effective experiments and focuses on the practical needs of applied statisticians and experimenters engaged in design, implementation and analysis. Emphasising the logical principles of statistical design, rather than mathematical calculation, the authors demonstrate how all available information can be used to extract the clearest answers to many questions. The principles are illustrated with a wide range of examples drawn from real experiments in medicine, industry, agriculture and many experimental disciplines. Numerous exercises are given to help the reader practise techniques and to appreciate the difference that good design can make to an experimental research project. Based on Roger Mead's excellent Design of Experiments, this new edition is thoroughly revised and updated to include modern methods relevant to applications in industry, engineering and modern biology. It also contains seven new chapters on contemporary topics, including restricted randomisation and fractional replication.

Download or read book Statistical Analysis of Designed Experiments Third Edition written by Helge Toutenburg and published by Springer Science & Business Media. This book was released on 2009-12-24 with total page 625 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the third revised and updated English edition of the German textbook \Versuchsplanung und Modellwahl" by Helge Toutenburg which was based on more than 15 years experience of lectures on the course \- sign of Experiments" at the University of Munich and interactions with the statisticians from industries and other areas of applied sciences and en- neering. This is a type of resource/ reference book which contains statistical methods used by researchers in applied areas. Because of the diverse ex- ples combined with software demonstrations it is also useful as a textbook in more advanced courses, The applications of design of experiments have seen a signi?cant growth in the last few decades in di?erent areas like industries, pharmaceutical sciences, medical sciences, engineering sciences etc. The second edition of this book received appreciation from academicians, teachers, students and applied statisticians. As a consequence, Springer-Verlag invited Helge Toutenburg to revise it and he invited Shalabh for the third edition of the book. In our experience with students, statisticians from industries and - searchers from other ?elds of experimental sciences, we realized the importance of several topics in the design of experiments which will - crease the utility of this book. Moreover we experienced that these topics are mostly explained only theoretically in most of the available books.