Computer Aided Multivariate Analysis Fourth Edition
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Computer Aided Multivariate Analysis Fourth Edition
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Author : Abdelmonem Afifi
language : en
Publisher: CRC Press
Release Date : 2003-12-29
Computer Aided Multivariate Analysis Fourth Edition written by Abdelmonem Afifi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-12-29 with Mathematics categories.
Computer-Aided Multivariate Analysis, Fourth Edition enables researchers and students with limited mathematical backgrounds to understand the concepts underlying multivariate statistical analysis, perform analysis using statistical packages, and understand the output. New topics include Loess and Poisson regression, nominal and ordinal logistic regression, interpretation of interactions in logistic and survival analysis, and imputation for missing values. This book includes new exercises and references, and updated options in the latest versions of the statistical packages. All data sets and codebooks are available for download. The authors explain the assumptions made in performing each analysis and test, how to determine if your data meets those assumptions, and what to do if they do not. What to Watch out for sections in each chapter warn of common difficulties. By reading this text, you will know what method to use with your data set, how to get the results, and how to interpret them and explain them to others. New in the Fourth Edition: Expanded explanation of checking for goodness of fit in logistic regression and survival analysis Kaplan-Meier estimates of survival curves, formal tests for comparing survival between groups, interactions and the use of time-dependent covariates in survival analysis Expanded discussion of how to handle missing values Latest features of the S-PLUS package in addition to SAS, SPSS, STATA, and STATISTICA for multivariate analysis Data sets for the problems are available at the CRC web site: http://www.crcpress.com/product/isbn/9781584883081 Commands and output for examples used in the text for each statistical package are available at the UCLA web site: http://www.ats.ucla.edu/stat/examples/cama4/
Computer Aided Multivariate Analysis Fourth Edition
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Author : Abdelmonem Afifi
language : en
Publisher: Chapman and Hall/CRC
Release Date : 1996-06-01
Computer Aided Multivariate Analysis Fourth Edition written by Abdelmonem Afifi and has been published by Chapman and Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-06-01 with Mathematics categories.
Increasingly, researchers need to perform multivariate statistical analyses on their data. Unfortunately, a lack of mathematical training prevents many from taking advantage of these advanced techniques, in part, because books focus on the theory & neglect to explain how to perform & interpret multivariate analyses on real-life data. For years, Afifi & Clark's Computer-Aided Multivariate Analysis has been a welcome exception-helping researchers choose the appropriate analyses for their data, carry them out, & interpret the results. Only a limited knowledge of statistics is assumed, & geometrical & graphical explanations are used to explain what the analyses do. However, the basic model is always given, & assumptions are discussed. Reflecting the increased emphasis on computers, the Third Edition includes three additional statistical packages written for the personal computer. The authors also discuss data entry, database management, data screening, data transformations, as well as multivariate data analysis. Another new chapter focuses on log-linear analysis of multi-way frequency tables. Students in a wide range of fields-ranging from psychology, sociology, & physical sciences to public health & biomedical science-will find Computer-Aided Multivariate Analysis especially informative & enlightening.
Computer Aided Multivariate Analysis
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Author : Abdelmonem A. Afifi
language : en
Publisher: Van Nostrand Reinhold Company
Release Date : 1990
Computer Aided Multivariate Analysis written by Abdelmonem A. Afifi and has been published by Van Nostrand Reinhold Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Mathematics categories.
Computer Aided Multivariate Analysis
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Author : Abdelmonem Abdelaziz Afifi
language : en
Publisher:
Release Date : 1996
Computer Aided Multivariate Analysis written by Abdelmonem Abdelaziz Afifi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Multivariate analysis categories.
Computer Aided Multivariate Analysis
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Author : Abdelmonem Abdelaziz Afifi
language : en
Publisher:
Release Date : 1996
Computer Aided Multivariate Analysis written by Abdelmonem Abdelaziz Afifi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Multivariate analysis categories.
Time Series Analysis
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Author : Henrik Madsen
language : en
Publisher: CRC Press
Release Date : 2007-11-28
Time Series Analysis written by Henrik Madsen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-11-28 with Mathematics categories.
With a focus on analyzing and modeling linear dynamic systems using statistical methods, Time Series Analysis formulates various linear models, discusses their theoretical characteristics, and explores the connections among stochastic dynamic models. Emphasizing the time domain description, the author presents theorems to highlight the most important results, proofs to clarify some results, and problems to illustrate the use of the results for modeling real-life phenomena. The book first provides the formulas and methods needed to adapt a second-order approach for characterizing random variables as well as introduces regression methods and models, including the general linear model. It subsequently covers linear dynamic deterministic systems, stochastic processes, time domain methods where the autocorrelation function is key to identification, spectral analysis, transfer-function models, and the multivariate linear process. The text also describes state space models and recursive and adaptivemethods. The final chapter examines a host of practical problems, including the predictions of wind power production and the consumption of medicine, a scheduling system for oil delivery, and the adaptive modeling of interest rates. Concentrating on the linear aspect of this subject, Time Series Analysis provides an accessible yet thorough introduction to the methods for modeling linear stochastic systems. It will help you understand the relationship between linear dynamic systems and linear stochastic processes.
Practical Multivariate Analysis
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Author : Abdelmonem Afifi
language : en
Publisher: CRC Press
Release Date : 2011-07-05
Practical Multivariate Analysis written by Abdelmonem Afifi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-07-05 with Mathematics categories.
This new version of the bestselling Computer-Aided Multivariate Analysis has been appropriately renamed to better characterize the nature of the book. Taking into account novel multivariate analyses as well as new options for many standard methods, Practical Multivariate Analysis, Fifth Edition shows readers how to perform multivariate statistical
Design Of Experiments
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Author : Max Morris
language : en
Publisher: CRC Press
Release Date : 2010-07-27
Design Of Experiments written by Max Morris and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-27 with Mathematics categories.
Offering deep insight into the connections between design choice and the resulting statistical analysis, Design of Experiments: An Introduction Based on Linear Models explores how experiments are designed using the language of linear statistical models. The book presents an organized framework for understanding the statistical aspects of experimental design as a whole within the structure provided by general linear models, rather than as a collection of seemingly unrelated solutions to unique problems. The core material can be found in the first thirteen chapters. These chapters cover a review of linear statistical models, completely randomized designs, randomized complete blocks designs, Latin squares, analysis of data from orthogonally blocked designs, balanced incomplete block designs, random block effects, split-plot designs, and two-level factorial experiments. The remainder of the text discusses factorial group screening experiments, regression model design, and an introduction to optimal design. To emphasize the practical value of design, most chapters contain a short example of a real-world experiment. Details of the calculations performed using R, along with an overview of the R commands, are provided in an appendix. This text enables students to fully appreciate the fundamental concepts and techniques of experimental design as well as the real-world value of design. It gives them a profound understanding of how design selection affects the information obtained in an experiment.
Extending The Linear Model With R
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Author : Julian J. Faraway
language : en
Publisher: CRC Press
Release Date : 2016-02-10
Extending The Linear Model With R written by Julian J. Faraway and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-02-10 with Mathematics categories.
Linear models are central to the practice of statistics and form the foundation of a vast range of statistical methodologies. Julian J. Faraway's critically acclaimed Linear Models with R examined regression and analysis of variance, demonstrated the different methods available, and showed in which situations each one applies. Following in those footsteps, Extending the Linear Model with R surveys the techniques that grow from the regression model, presenting three extensions to that framework: generalized linear models (GLMs), mixed effect models, and nonparametric regression models. The author's treatment is thoroughly modern and covers topics that include GLM diagnostics, generalized linear mixed models, trees, and even the use of neural networks in statistics. To demonstrate the interplay of theory and practice, throughout the book the author weaves the use of the R software environment to analyze the data of real examples, providing all of the R commands necessary to reproduce the analyses. All of the data described in the book is available at http://people.bath.ac.uk/jjf23/ELM/ Statisticians need to be familiar with a broad range of ideas and techniques. This book provides a well-stocked toolbox of methodologies, and with its unique presentation of these very modern statistical techniques, holds the potential to break new ground in the way graduate-level courses in this area are taught.
Modeling And Analysis Of Stochastic Systems
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Author : Vidyadhar G. Kulkarni
language : en
Publisher: CRC Press
Release Date : 2009-12-18
Modeling And Analysis Of Stochastic Systems written by Vidyadhar G. Kulkarni and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-12-18 with Business & Economics categories.
Based on the author's more than 25 years of teaching experience, Modeling and Analysis of Stochastic Systems, Second Edition covers the most important classes of stochastic processes used in the modeling of diverse systems, from supply chains and inventory systems to genetics and biological systems. For each class of stochastic process, the text includes its definition, characterization, applications, transient and limiting behavior, first passage times, and cost/reward models. Along with reorganizing the material, this edition revises and adds new exercises and examples. New to the second edition: a new chapter on diffusion processes that gives an accessible and non-measure-theoretic treatment with applications to finance; a more streamlined, application-oriented approach to renewal, regenerative, and Markov regenerative processes; and, two appendices that collect relevant results from analysis and differential and difference equations. Rather than offer special tricks that work in specific problems, this book provides thorough coverage of general tools that enable the solution and analysis of stochastic models. After mastering the material in the text, students will be well-equipped to build and analyze useful stochastic models for various situations. A collection of MATLAB[registered]-based programs can be downloaded from the author's website and a solutions manual is available for qualifying instructors.