Fundamentals Of Exploratory Analysis Of Variance
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Fundamentals Of Exploratory Analysis Of Variance
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Author : David C. Hoaglin
language : en
Publisher: John Wiley & Sons
Release Date : 2009-09-25
Fundamentals Of Exploratory Analysis Of Variance written by David C. Hoaglin and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-25 with Mathematics categories.
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.
Sea Fundamentals Of Exploratory Analysis Of Variance
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Author : Hoaglin
language : en
Publisher:
Release Date : 1994-10-01
Sea Fundamentals Of Exploratory Analysis Of Variance written by Hoaglin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994-10-01 with categories.
The Collected Works Of John W Tukey
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Author : D.R. Cox
language : en
Publisher: CRC Press
Release Date : 1992-04-01
The Collected Works Of John W Tukey written by D.R. Cox and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992-04-01 with Mathematics categories.
These papers illustrate important features characteristic of John Tukey's work, namely the desire to look beyond or beneath conventional set structures, the wish to detect and deal with anomalous behavior, and great technical ingenuity.
Understanding Robust And Exploratory Data Analysis
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Author : David C. Hoaglin
language : en
Publisher: John Wiley & Sons
Release Date : 2000-06-02
Understanding Robust And Exploratory Data Analysis written by David C. Hoaglin and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-06-02 with Mathematics categories.
Originally published in hardcover in 1982, this book is now offered in a Wiley Classics Library edition. A contributed volume, edited by some of the preeminent statisticians of the 20th century, Understanding of Robust and Exploratory Data Analysis explains why and how to use exploratory data analysis and robust and resistant methods in statistical practice.
The Analysis Of Variance
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Author : Hardeo Sahai
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
The Analysis Of Variance written by Hardeo Sahai and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
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.
Applied Analysis Of Variance In Behavioral Science
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Author : Lynne Edwards
language : en
Publisher: CRC Press
Release Date : 1993-06-16
Applied Analysis Of Variance In Behavioral Science written by Lynne Edwards and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993-06-16 with Mathematics categories.
A reference devoted to the discussion of analysis of variance (ANOVA) techniques. It presents ANOVA as a research design, a collection of statistical models, an analysis model, and an arithmetic summary of data. Discussion focuses primarily on univariate data, but multivariate generalizations are to
Anova And Ancova
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Author : Andrew Rutherford
language : en
Publisher: John Wiley & Sons
Release Date : 2012-08-29
Anova And Ancova written by Andrew Rutherford and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-29 with Mathematics categories.
Provides an in-depth treatment of ANOVA and ANCOVA techniques from a linear model perspective ANOVA and ANCOVA: A GLM Approach provides a contemporary look at the general linear model (GLM) approach to the analysis of variance (ANOVA) of one- and two-factor psychological experiments. With its organized and comprehensive presentation, the book successfully guides readers through conventional statistical concepts and how to interpret them in GLM terms, treating the main single- and multi-factor designs as they relate to ANOVA and ANCOVA. The book begins with a brief history of the separate development of ANOVA and regression analyses, and then goes on to demonstrate how both analyses are incorporated into the understanding of GLMs. This new edition now explains specific and multiple comparisons of experimental conditions before and after the Omnibus ANOVA, and describes the estimation of effect sizes and power analyses leading to the determination of appropriate sample sizes for experiments to be conducted. Topics that have been expanded upon and added include: Discussion of optimal experimental designs Different approaches to carrying out the simple effect analyses and pairwise comparisons with a focus on related and repeated measure analyses The issue of inflated Type 1 error due to multiple hypotheses testing Worked examples of Shaffer's R test, which accommodates logical relations amongst hypotheses ANOVA and ANCOVA: A GLM Approach, Second Edition is an excellent book for courses on linear modeling at the graduate level. It is also a suitable reference for researchers and practitioners in the fields of psychology and the biomedical and social sciences.
Beyond Anova Basics Of Applied Statistics
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Author : Rupert G. Miller
language : en
Publisher: John Wiley & Sons
Release Date : 1986
Beyond Anova Basics Of Applied Statistics written by Rupert G. Miller and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986 with Mathematics categories.
This book goes beyond specific methods in specific applications to consider the full range of techniques which can be used to solve a statistical problem. This applied text treats general topics such as one- and two-sample problems, one- and two-way classifications, regression analysis, ratios and variances. It includes helpful problem-solving hints and references along with theoretical and real-life exercises at the end of each chapter.
Theoretical Foundations Of Functional Data Analysis With An Introduction To Linear Operators
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Author : Tailen Hsing
language : en
Publisher: John Wiley & Sons
Release Date : 2015-05-06
Theoretical Foundations Of Functional Data Analysis With An Introduction To Linear Operators written by Tailen Hsing and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-06 with Mathematics categories.
Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators provides a uniquely broad compendium of the key mathematical concepts and results that are relevant for the theoretical development of functional data analysis (FDA). The self–contained treatment of selected topics of functional analysis and operator theory includes reproducing kernel Hilbert spaces, singular value decomposition of compact operators on Hilbert spaces and perturbation theory for both self–adjoint and non self–adjoint operators. The probabilistic foundation for FDA is described from the perspective of random elements in Hilbert spaces as well as from the viewpoint of continuous time stochastic processes. Nonparametric estimation approaches including kernel and regularized smoothing are also introduced. These tools are then used to investigate the properties of estimators for the mean element, covariance operators, principal components, regression function and canonical correlations. A general treatment of canonical correlations in Hilbert spaces naturally leads to FDA formulations of factor analysis, regression, MANOVA and discriminant analysis. This book will provide a valuable reference for statisticians and other researchers interested in developing or understanding the mathematical aspects of FDA. It is also suitable for a graduate level special topics course.
Foundations Of Linear And Generalized Linear Models
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Author : Alan Agresti
language : en
Publisher: John Wiley & Sons
Release Date : 2015-01-15
Foundations Of Linear And Generalized Linear Models written by Alan Agresti and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-15 with Mathematics categories.
A valuable overview of the most important ideas and results in statistical modeling Written by a highly-experienced author, Foundations of Linear and Generalized Linear Models is a clear and comprehensive guide to the key concepts and results of linearstatistical models. The book presents a broad, in-depth overview of the most commonly usedstatistical models by discussing the theory underlying the models, R software applications,and examples with crafted models to elucidate key ideas and promote practical modelbuilding. The book begins by illustrating the fundamentals of linear models, such as how the model-fitting projects the data onto a model vector subspace and how orthogonal decompositions of the data yield information about the effects of explanatory variables. Subsequently, the book covers the most popular generalized linear models, which include binomial and multinomial logistic regression for categorical data, and Poisson and negative binomial loglinear models for count data. Focusing on the theoretical underpinnings of these models, Foundations ofLinear and Generalized Linear Models also features: An introduction to quasi-likelihood methods that require weaker distributional assumptions, such as generalized estimating equation methods An overview of linear mixed models and generalized linear mixed models with random effects for clustered correlated data, Bayesian modeling, and extensions to handle problematic cases such as high dimensional problems Numerous examples that use R software for all text data analyses More than 400 exercises for readers to practice and extend the theory, methods, and data analysis A supplementary website with datasets for the examples and exercises An invaluable textbook for upper-undergraduate and graduate-level students in statistics and biostatistics courses, Foundations of Linear and Generalized Linear Models is also an excellent reference for practicing statisticians and biostatisticians, as well as anyone who is interested in learning about the most important statistical models for analyzing data.