Download or read book Statistical Inference and Design of Experiments written by Meena R. Satam and published by Alpha Science Int'l Ltd.. This book was released on 1999 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this volume is to be well informed about recent developments in theoretical and applied aspects of Statistics. A major part of this book comprises of statistical inference and design of experiments.
Download or read book The Design of Experiments written by Sir Ronald Aylmer Fisher and published by . This book was released on 1974 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistical Methods Experimental Design and Scientific Inference written by R. A. Fisher and published by OUP Oxford. This book was released on 1990-04-19 with total page 832 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Experimental Design and Statistics written by Steve Miller and published by Routledge. This book was released on 2005-07-25 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: For this second edition, this best-selling textbook has been revised, the coverage of two-sample tests extended, and new sections added introducing one-sample tests, linear regression, and the product-moment correlation coefficient.
Download or read book Understanding Statistics and Experimental Design written by Michael H. Herzog and published by Springer. This book was released on 2019-08-13 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Models for Probability and Statistical Inference written by James H. Stapleton and published by John Wiley & Sons. This book was released on 2007-12-14 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readers Models for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the book, readers acquire the fundamentals needed to advance to more specialized topics, such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping. Ideal as a textbook for a two-semester sequence on probability and statistical inference, early chapters provide coverage on probability and include discussions of: discrete models and random variables; discrete distributions including binomial, hypergeometric, geometric, and Poisson; continuous, normal, gamma, and conditional distributions; and limit theory. Since limit theory is usually the most difficult topic for readers to master, the author thoroughly discusses modes of convergence of sequences of random variables, with special attention to convergence in distribution. The second half of the book addresses statistical inference, beginning with a discussion on point estimation and followed by coverage of consistency and confidence intervals. Further areas of exploration include: distributions defined in terms of the multivariate normal, chi-square, t, and F (central and non-central); the one- and two-sample Wilcoxon test, together with methods of estimation based on both; linear models with a linear space-projection approach; and logistic regression. Each section contains a set of problems ranging in difficulty from simple to more complex, and selected answers as well as proofs to almost all statements are provided. An abundant amount of figures in addition to helpful simulations and graphs produced by the statistical package S-Plus(r) are included to help build the intuition of readers.
Download or read book Statistical Inference as Severe Testing written by Deborah G. Mayo and published by Cambridge University Press. This book was released on 2018-09-20 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.
Download or read book Statistical Design written by George Casella and published by Springer Science & Business Media. This book was released on 2008-04-03 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical design is one of the fundamentals of our subject, being at the core of the growth of statistics during the previous century. In this book the basic theoretical underpinnings are covered. It describes the principles that drive good designs and good statistics. Design played a key role in agricultural statistics and set down principles of good practice, principles that still apply today. Statistical design is all about understanding where the variance comes from, and making sure that is where the replication is. Indeed, it is probably correct to say that these principles are even more important today.
Download or read book Introduction to Statistical Methods Design of Experiments and Statistical Quality Control written by Dharmaraja Selvamuthu and published by Springer. This book was released on 2018-09-03 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an accessible presentation of concepts from probability theory, statistical methods, the design of experiments and statistical quality control. It is shaped by the experience of the two teachers teaching statistical methods and concepts to engineering students, over a decade. Practical examples and end-of-chapter exercises are the highlights of the text as they are purposely selected from different fields. Statistical principles discussed in the book have great relevance in several disciplines like economics, commerce, engineering, medicine, health-care, agriculture, biochemistry, and textiles to mention a few. A large number of students with varied disciplinary backgrounds need a course in basics of statistics, the design of experiments and statistical quality control at an introductory level to pursue their discipline of interest. No previous knowledge of probability or statistics is assumed, but an understanding of calculus is a prerequisite. The whole book serves as a master level introductory course in all the three topics, as required in textile engineering or industrial engineering. Organised into 10 chapters, the book discusses three different courses namely statistics, the design of experiments and quality control. Chapter 1 is the introductory chapter which describes the importance of statistical methods, the design of experiments and statistical quality control. Chapters 2–6 deal with statistical methods including basic concepts of probability theory, descriptive statistics, statistical inference, statistical test of hypothesis and analysis of correlation and regression. Chapters 7–9 deal with the design of experiments including factorial designs and response surface methodology, and Chap. 10 deals with statistical quality control.
Download or read book Statistical Principles in Experimental Design written by B. J. Winer and published by New York; Montreal : McGraw-Hill. This book was released on 1971 with total page 934 pages. Available in PDF, EPUB and Kindle. Book excerpt: A revision of this classic statistics text for first-year graduate students in psychology, education and related social sciences. The two new authors are former students of Winer's. They have updated, rewritten and reorganized the text to fit the course as it is now taught.
Download or read book A First Course in Design and Analysis of Experiments written by Gary W. Oehlert and published by . This book was released on 2010 with total page 659 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Oehlert’s text is suitable for either a service course for non-statistics graduate students or for statistics majors. Unlike most texts for the one-term grad/upper level course on experimental design, Oehlert’s new book offers a superb balance of both analysis and design, presenting three practical themes to students: when to use various designs; how to analyze the results; how to recognize various design options. Also, unlike other older texts, the book is fully oriented toward the use of statistical software in analyzing experiments"--Publisher's description.
Download or read book Design and Analysis of Experiments written by Douglas C. Montgomery and published by Wiley. This book was released on 2005 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This bestselling professional reference has helped over 100,000 engineers and scientists with the success of their experiments. The new edition includes more software examples taken from the three most dominant programs in the field: Minitab, JMP, and SAS. Additional material has also been added in several chapters, including new developments in robust design and factorial designs. New examples and exercises are also presented to illustrate the use of designed experiments in service and transactional organizations. Engineers will be able to apply this information to improve the quality and efficiency of working systems.
Download or read book Introduction to Statistical Investigations written by Nathan Tintle and published by Wiley Global Education. This book was released on 2015-12-17 with total page 696 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Statistical Investigations leads students to learn about the process of conducting statistical investigations from data collection, to exploring data, to statistical inference, to drawing appropriate conclusions. The text is designed for a one-semester introductory statistics course. It focuses on genuine research studies, active learning, and effective use of technology. Simulations and randomization tests introduce statistical inference, yielding a strong conceptual foundation that bridges students to theory-based inference approaches. Repetition allows students to see the logic and scope of inference. This implementation follows the GAISE recommendations endorsed by the American Statistical Association.
Download or read book Statistical Design written by George Casella and published by Springer Science & Business Media. This book was released on 2008-04-20 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical design is one of the fundamentals of our subject, being at the core of the growth of statistics during the previous century. In this book the basic theoretical underpinnings are covered. It describes the principles that drive good designs and good statistics. Design played a key role in agricultural statistics and set down principles of good practice, principles that still apply today. Statistical design is all about understanding where the variance comes from, and making sure that is where the replication is. Indeed, it is probably correct to say that these principles are even more important today.
Download or read book Bayesian Statistics for Experimental Scientists written by Richard A. Chechile and published by MIT Press. This book was released on 2020-09-08 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the Bayesian approach to statistical inference that demonstrates its superiority to orthodox frequentist statistical analysis. This book offers an introduction to the Bayesian approach to statistical inference, with a focus on nonparametric and distribution-free methods. It covers not only well-developed methods for doing Bayesian statistics but also novel tools that enable Bayesian statistical analyses for cases that previously did not have a full Bayesian solution. The book's premise is that there are fundamental problems with orthodox frequentist statistical analyses that distort the scientific process. Side-by-side comparisons of Bayesian and frequentist methods illustrate the mismatch between the needs of experimental scientists in making inferences from data and the properties of the standard tools of classical statistics. The book first covers elementary probability theory, the binomial model, the multinomial model, and methods for comparing different experimental conditions or groups. It then turns its focus to distribution-free statistics that are based on having ranked data, examining data from experimental studies and rank-based correlative methods. Each chapter includes exercises that help readers achieve a more complete understanding of the material. The book devotes considerable attention not only to the linkage of statistics to practices in experimental science but also to the theoretical foundations of statistics. Frequentist statistical practices often violate their own theoretical premises. The beauty of Bayesian statistics, readers will learn, is that it is an internally coherent system of scientific inference that can be proved from probability theory.
Download or read book An Introduction to the Design Analysis of Experiments written by George C. Canavos and published by Pearson. This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to the Design & Analysis of Experiments introduces readers to the design and analysis of experiments. It is ideal for a one-semester, upper-level undergraduate course for majors in statistics and other mathematical sciences, natural sciences, and engineering. It may also serve appropriate graduate courses in disciplines such as business, health sciences, and social sciences. This book assumes that the reader has completed a two-semester sequence in the application of probability and statistical inference. KEY TOPICS An Introduction to the Design of Experiments; Investigating a Single Factor: Completely Randomized Experiments; Investigating a Single Factor: Randomized Complete and Incomplete Block and Latin Square Designs; Factorial Experiments: Completely Randomized Designs; Factorial Experiments: Randomized Block and Latin Square Designs; Nested Factorial Experiments and Repeated Measures Designs; 2f and 3f Factorial Experiments; Confounding in 2f and 3f Factorial Experiments; Fractional Factorial Experiments0; Regression Analysis: The General Linear Model; Response Surface Designs for First and Second-Order Models. MARKET For all readers interested in experimental design.
Download or read book Statistics for Experimenters written by George E. P. Box and published by Wiley-Interscience. This book was released on 1978-07-06 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces the philosophy of experimentation and the part that statistics play in experimentation. Emphasizes the need to develop a capability for ``statistical thinking'' by using examples drawn from actual case studies.
