Download or read book The Analysis of Variance written by Hardeo Sahai and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 766 pages. Available in PDF, EPUB and Kindle. Book excerpt: The analysis of variance (ANOYA) models have become one of the most widely used tools of modern statistics for analyzing multifactor data. The ANOYA models provide versatile statistical tools for studying the relationship between a dependent variable and one or more independent variables. The ANOYA mod els are employed to determine whether different variables interact and which factors or factor combinations are most important. They are appealing because they provide a conceptually simple technique for investigating statistical rela tionships among different independent variables known as factors. Currently there are several texts and monographs available on the sub ject. However, some of them such as those of Scheffe (1959) and Fisher and McDonald (1978), are written for mathematically advanced readers, requiring a good background in calculus, matrix algebra, and statistical theory; whereas others such as Guenther (1964), Huitson (1971), and Dunn and Clark (1987), although they assume only a background in elementary algebra and statistics, treat the subject somewhat scantily and provide only a superficial discussion of the random and mixed effects analysis of variance.

Download or read book Analysis of Variance Design and Regression written by Ronald Christensen and published by CRC Press. This book was released on 1996-06-01 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text presents a comprehensive treatment of basic statistical methods and their applications. It focuses on the analysis of variance and regression, but also addressing basic ideas in experimental design and count data. The book has four connecting themes: similarity of inferential procedures, balanced one-way analysis of variance, comparison of models, and checking assumptions. Most inferential procedures are based on identifying a scalar parameter of interest, estimating that parameter, obtaining the standard error of the estimate, and identifying the appropriate reference distribution. Given these items, the inferential procedures are identical for various parameters. Balanced one-way analysis of variance has a simple, intuitive interpretation in terms of comparing the sample variance of the group means with the mean of the sample variance for each group. All balanced analysis of variance problems are considered in terms of computing sample variances for various group means. Comparing different models provides a structure for examining both balanced and unbalanced analysis of variance problems and regression problems. Checking assumptions is presented as a crucial part of every statistical analysis. Examples using real data from a wide variety of fields are used to motivate theory. Christensen consistently examines residual plots and presents alternative analyses using different transformation and case deletions. Detailed examination of interactions, three factor analysis of variance, and a split-plot design with four factors are included. The numerous exercises emphasize analysis of real data. Senior undergraduate and graduate students in statistics and graduate students in other disciplines using analysis of variance, design of experiments, or regression analysis will find this book useful.

Download or read book Two Way Analysis of Variance written by Thomas W. MacFarland and published by Springer Science & Business Media. This book was released on 2011-12-09 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: ​In statistics, analysis of variance (ANOVA) is a collection of statistical models used to distinguish between an observed variance in a particular variable and its component parts. In its simplest form, ANOVA provides a statistical test of whether or not the means of several groups are all equal, and therefore generalizes a test between these groups. One test often used by statisticians and researchers in their work is the Two-Way ANOVA, which determines the differences--and possible interactions--when variables are presented from the perspective of two or more categories. When a Two-Way ANOVA is implemented, it enables one to compare and contrast variables resulting from independent or joint actions. This brief provides guidance on how R can be used to facilitate Two-Way ANOVA for data analysis and graphical presentation. Along with instruction on the use of R and R syntax associated with Two-Way ANOVA, this brief will also reinforce the use of descriptive statistics and graphical figures to complement outcomes from parametric Two-Way ANOVA.

Download or read book Analysis of Variance in Experimental Design written by Harold R. Lindman and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: As an introductory textbook on the analysis of variance or a reference for the researcher, this text stresses applications rather than theory, but gives enough theory to enable the reader to apply the methods intelligently rather than mechanically. Comprehensive, and covering the important techniques in the field, including new methods of post hoc testing. The relationships between different research designs are emphasized, and these relationships are exploited to develop general principles which are generalized to the analyses of a large number of seemingly differentdesigns. Primarily for graduate students in any field where statistics are used.

Download or read book Advanced Analysis of Variance written by Chihiro Hirotsu and published by John Wiley & Sons. This book was released on 2017-08-14 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introducing a revolutionary new model for the statistical analysis of experimental data In this important book, internationally acclaimed statistician, Chihiro Hirotsu, goes beyond classical analysis of variance (ANOVA) model to offer a unified theory and advanced techniques for the statistical analysis of experimental data. Dr. Hirotsu introduces the groundbreaking concept of advanced analysis of variance (AANOVA) and explains how the AANOVA approach exceeds the limitations of ANOVA methods to allow for global reasoning utilizing special methods of simultaneous inference leading to individual conclusions. Focusing on normal, binomial, and categorical data, Dr. Hirotsu explores ANOVA theory and practice and reviews current developments in the field. He then introduces three new advanced approaches, namely: testing for equivalence and non-inferiority; simultaneous testing for directional (monotonic or restricted) alternatives and change-point hypotheses; and analyses emerging from categorical data. Using real-world examples, he shows how these three recognizable families of problems have important applications in most practical activities involving experimental data in an array of research areas, including bioequivalence, clinical trials, industrial experiments, pharmaco-statistics, and quality control, to name just a few. • Written in an expository style which will encourage readers to explore applications for AANOVA techniques in their own research • Focuses on dealing with real data, providing real-world examples drawn from the fields of statistical quality control, clinical trials, and drug testing • Describes advanced methods developed and refined by the author over the course of his long career as research engineer and statistician • Introduces advanced technologies for AANOVA data analysis that build upon the basic ANOVA principles and practices Introducing a breakthrough approach to statistical analysis which overcomes the limitations of the ANOVA model, Advanced Analysis of Variance is an indispensable resource for researchers and practitioners working in fields within which the statistical analysis of experimental data is a crucial research component. Chihiro Hirotsu is a Senior Researcher at the Collaborative Research Center, Meisei University, and Professor Emeritus at the University of Tokyo. He is a fellow of the American Statistical Association, an elected member of the International Statistical Institute, and he has been awarded the Japan Statistical Society Prize (2005) and the Ouchi Prize (2006). His work has been published in Biometrika, Biometrics, and Computational Statistics & Data Analysis, among other premier research journals.

Download or read book The Analysis of Variance written by Henry Scheffé and published by John Wiley & Sons. This book was released on 1999-03-05 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Originally published in 1959, this classic volume has had a major impact on generations of statisticians. Newly issued in the Wiley Classics Series, the book examines the basic theory of analysis of variance by considering several different mathematical models. Part I looks at the theory of fixed-effects models with independent observations of equal variance, while Part II begins to explore the analysis of variance in the case of other models.

Download or read book Analysis of Variance for Functional Data written by Jin-Ting Zhang and published by CRC Press. This book was released on 2013-06-18 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite research interest in functional data analysis in the last three decades, few books are available on the subject. Filling this gap, Analysis of Variance for Functional Data presents up-to-date hypothesis testing methods for functional data analysis. The book covers the reconstruction of functional observations, functional ANOVA, functional l

Download or read book A Student s Guide to Analysis of Variance written by Maxwell J. Roberts and published by Routledge. This book was released on 2014-06-03 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the investigation of human behaviour, statistical techniques are employed widely in the social sciences. Whilst introductory statistics courses cover essential techniques, the complexities of behaviour demand that more flexible and comprehensive methods are also employed. Analysis of Variance (ANOVA) has become one of the most common of these and it is therefore essential for both student and researcher to have a thorough understanding of it. A Student's Guide to Analysis of Variance covers a range of statistical techniques associated with ANOVA, including single and multiple factor designs, various follow-up procedures such as post-hoc tests, and how to make sense of interactions. Suggestions on the best use of techniques and advice on how to avoid the pitfalls are included, along with guidelines on the writing of formal reports. Introductory level topics such as standard deviation, standard error and t-tests are revised, making this book an invaluable aid to all students for whom ANOVA is a compulsory topic. It will also serve as a useful refresher for the more advanced student and practising researcher.

Download or read book Fundamentals of Exploratory Analysis of Variance written by David C. Hoaglin and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: The analysis of variance is presented as an exploratory component of data analysis, while retaining the customary least squares fitting methods. Balanced data layouts are used to reveal key ideas and techniques for exploration. The approach emphasizes both the individual observations and the separate parts that the analysis produces. Most chapters include exercises and the appendices give selected percentage points of the Gaussian, t, F chi-squared and studentized range distributions.

Download or read book Analysis of Variance and Covariance written by C. Patrick Doncaster and published by Cambridge University Press. This book was released on 2007-08-30 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analysis of variance (ANOVA) is a core technique for analysing data in the Life Sciences. This reference book bridges the gap between statistical theory and practical data analysis by presenting a comprehensive set of tables for all standard models of analysis of variance and covariance with up to three treatment factors. The book will serve as a tool to help post-graduates and professionals define their hypotheses, design appropriate experiments, translate them into a statistical model, validate the output from statistics packages and verify results. The systematic layout makes it easy for readers to identify which types of model best fit the themes they are investigating, and to evaluate the strengths and weaknesses of alternative experimental designs. In addition, a concise introduction to the principles of analysis of variance and covariance is provided, alongside worked examples illustrating issues and decisions faced by analysts.

Download or read book Beyond ANOVA written by Rupert G. Miller, Jr. and published by CRC Press. This book was released on 1997-01-01 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Renowned statistician R.G. Miller set the pace for statistics students with Beyond ANOVA: Basics of Applied Statistics. Designed to show students how to work with a set of "real world data," Miller's text goes beyond any specific discipline, and considers a whole variety of techniques from ANOVA to empirical Bayes methods; the jackknife, bootstrap methods; and the James-Stein estimator. This reissue of Miller's classic book has been revised by professors at Stanford University, California. As before, one of the main strengths of Beyond ANOVA is its promotion of the use of the most straightforward data analysis methods-giving students a viable option, instead of resorting to complicated and unnecessary tests. Assuming a basic background in statistics, Beyond ANOVA is written for undergraduates and graduate statistics students. Its approach will also be valued by biologists, social scientists, engineers, and anyone who may wish to handle their own data analysis.

Download or read book Multivariate Analysis of Variance written by James H. Bray and published by SAGE. This book was released on 1985 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bray's monograph considers the multivariate form of analysis of variance (MANOVA). It is a technique which can be used in such different academic disciplines as psychology, sociology, biology, and education.

Download or read book Introduction to Analysis of Variance written by J. Rick Turner and published by SAGE Publications. This book was released on 2001-04-13 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: Having trouble finding a book that shows you not only how to analyze data but also how to collect the data appropriately and fully interpret the analysis, too? Here′s a new book that does all this in a particularly readable fashion. Turner and Thayer′s text: Shows how to design an experiment in the best possible way to investigate the topic of interest Explains which associated analysis will best answer your research question Demonstrates how to conduct the analysis and then fully interpret the results in the context of your research question Organized so that the reader moves from the simplest type of design to more complex ones, the authors introduce five different kinds of ANOVA techniques and explain which design/analysis is appropriate to answer specific questions. They show how to perform each analysis using only a calculator to provide the reader with a better "feel" for the analyses than simply seeing the mathematical answers on a computer print-out. The book concludes with tips for tests on ANOVA, and descriptions of how to use the knowledge gained from the text to determine the credibility of claims made and "statistics" presented in various types of reports.

Download or read book Analysis of Variance Via Confidence Intervals written by K D Bird and published by SAGE. This book was released on 2004-12-07 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analysis of variance - ANOVA - constitutes the main set of statistical methods through which undergraduate and postgraduate students carry out multivariate analysis. This textbook adopts an innovative approach to ANOVA, placing emphasis on confidence intervals rather than tests of significance.

Download or read book Analysis of Variance Design and Regression written by Ronald Christensen and published by CRC Press. This book was released on 2018-09-03 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analysis of Variance, Design, and Regression: Linear Modeling for Unbalanced Data, Second Edition presents linear structures for modeling data with an emphasis on how to incorporate specific ideas (hypotheses) about the structure of the data into a linear model for the data. The book carefully analyzes small data sets by using tools that are easily scaled to big data. The tools also apply to small relevant data sets that are extracted from big data. New to the Second Edition Reorganized to focus on unbalanced data Reworked balanced analyses using methods for unbalanced data Introductions to nonparametric and lasso regression Introductions to general additive and generalized additive models Examination of homologous factors Unbalanced split plot analyses Extensions to generalized linear models R, Minitab®, and SAS code on the author’s website The text can be used in a variety of courses, including a yearlong graduate course on regression and ANOVA or a data analysis course for upper-division statistics students and graduate students from other fields. It places a strong emphasis on interpreting the range of computer output encountered when dealing with unbalanced data.

Download or read book Analysis of Variance Designs written by Glenn Gamst and published by . This book was released on 2008 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook explains ANOVA designs for advanced undergraduates and graduate students in the behavioural sciences.

Download or read book Mean Variance Analysis in Portfolio Choice and Capital Markets written by Harry M. Markowitz and published by John Wiley & Sons. This book was released on 2000-02-15 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: In 1952, Harry Markowitz published "Portfolio Selection," a paper which revolutionized modern investment theory and practice. The paper proposed that, in selecting investments, the investor should consider both expected return and variability of return on the portfolio as a whole. Portfolios that minimized variance for a given expected return were demonstrated to be the most efficient. Markowitz formulated the full solution of the general mean-variance efficient set problem in 1956 and presented it in the appendix to his 1959 book, Portfolio Selection. Though certain special cases of the general model have become widely known, both in academia and among managers of large institutional portfolios, the characteristics of the general solution were not presented in finance books for students at any level. And although the results of the general solution are used in a few advanced portfolio optimization programs, the solution to the general problem should not be seen merely as a computing procedure. It is a body of propositions and formulas concerning the shapes and properties of mean-variance efficient sets with implications for financial theory and practice beyond those of widely known cases. The purpose of the present book, originally published in 1987, is to present a comprehensive and accessible account of the general mean-variance portfolio analysis, and to illustrate its usefulness in the practice of portfolio management and the theory of capital markets. The portfolio selection program in Part IV of the 1987 edition has been updated and contains exercises and solutions.