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Using Multivariate Statistics

Using Multivariate Statistics Author Barbara G. Tabachnick
ISBN-10 0134790545
Release 2018-07-02
Pages 1024
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For advanced undergraduate and graduate courses in Social Statistics. An in-depth introduction to today's most commonly used statistical and multivariate techniques Using Multivariate Statistics, 7th Edition presents complex statistical procedures in a way that is maximally useful and accessible to researchers who may not be statisticians. The authors focus on the benefits and limitations of applying a technique to a data set - when, why, and how to do it. Only a limited knowledge of higher-level mathematics is assumed. Students using this text will learn to conduct numerous types of multivariate statistical analyses; find the best technique to use; understand limitations to applications; and learn how to use SPSS and SAS syntax and output. 0134790545 / 9780134790541 Using Multivariate Statistics, 7/e



Using Multivariate Statistics

Using Multivariate Statistics Author Barbara G. Tabachnick
ISBN-10 9780205956227
Release 2012-10-11
Pages 1024
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This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. A Practical Approach to using Multivariate Analyses Using Multivariate Statistics, 6th edition provides advanced undergraduate as well as graduate students with a timely and comprehensive introduction to today's most commonly encountered statistical and multivariate techniques, while assuming only a limited knowledge of higher-level mathematics. This text’s practical approach focuses on the benefits and limitations of applications of a technique to a data set — when, why, and how to do it. Learning Goals Upon completing this book, readers should be able to: Learn to conduct numerous types of multivariate statistical analyses Find the best technique to use Understand Limitations to applications Learn how to use SPSS and SAS syntax and output Note: MySearchLab with eText does not come automatically packaged with this text. To purchase MySearchLab with eText, please visit www.mysearchlab.com or you can purchase a ValuePack of the text + MySearchLab with eText (at no additional cost). ValuePack ISBN-10: 0205885667 / ValuePack ISBN-13: 9780205885664



Using R With Multivariate Statistics

Using R With Multivariate Statistics Author Randall E. Schumacker
ISBN-10 9781483377988
Release 2015-06-18
Pages 408
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Using R with Multivariate Statistics by Randall E. Schumacker is a quick guide to using R, free-access software available for Windows and Mac operating systems that allows users to customize statistical analysis. Designed to serve as a companion to a more comprehensive text on multivariate statistics, this book helps students and researchers in the social and behavioral sciences get up to speed with using R. It provides data analysis examples, R code, computer output, and explanation of results for every multivariate statistical application included. In addition, R code for some of the data set examples used in more comprehensive texts is included, so students can run examples in R and compare results to those obtained using SAS, SPSS, or STATA. A unique feature of the book is the photographs and biographies of famous persons in the field of multivariate statistics.



Multivariate Statistical Methods

Multivariate Statistical Methods Author Bryan F.J. Manly
ISBN-10 9781498728997
Release 2016-11-03
Pages 269
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Multivariate Statistical Methods: A Primer provides an introductory overview of multivariate methods without getting too deep into the mathematical details. This fourth edition is a revised and updated version of this bestselling introductory textbook. It retains the clear and concise style of the previous editions of the book and focuses on examples from biological and environmental sciences. The major update with this edition is that R code has been included for each of the analyses described, although in practice any standard statistical package can be used. The original idea with this book still applies. This was to make it as short as possible and enable readers to begin using multivariate methods in an intelligent manner. With updated information on multivariate analyses, new references, and R code included, this book continues to provide a timely introduction to useful tools for multivariate statistical analysis.



Multivariate Statistical Quality Control Using R

Multivariate Statistical Quality Control Using R Author Edgar Santos-Fernández
ISBN-10 9781461454533
Release 2012-09-22
Pages 127
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​​​​​The intensive use of automatic data acquisition system and the use of cloud computing for process monitoring have led to an increased occurrence of industrial processes that utilize statistical process control and capability analysis. These analyses are performed almost exclusively with multivariate methodologies. The aim of this Brief is to present the most important MSQC techniques developed in R language. The book is divided into two parts. The first part contains the basic R elements, an introduction to statistical procedures, and the main aspects related to Statistical Quality Control (SQC). The second part covers the construction of multivariate control charts, the calculation of Multivariate Capability Indices.



Handbook of Applied Multivariate Statistics and Mathematical Modeling

Handbook of Applied Multivariate Statistics and Mathematical Modeling Author Howard E.A. Tinsley
ISBN-10 0080533566
Release 2000-05-22
Pages 721
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Multivariate statistics and mathematical models provide flexible and powerful tools essential in most disciplines. Nevertheless, many practicing researchers lack an adequate knowledge of these techniques, or did once know the techniques, but have not been able to keep abreast of new developments. The Handbook of Applied Multivariate Statistics and Mathematical Modeling explains the appropriate uses of multivariate procedures and mathematical modeling techniques, and prescribe practices that enable applied researchers to use these procedures effectively without needing to concern themselves with the mathematical basis. The Handbook emphasizes using models and statistics as tools. The objective of the book is to inform readers about which tool to use to accomplish which task. Each chapter begins with a discussion of what kinds of questions a particular technique can and cannot answer. As multivariate statistics and modeling techniques are useful across disciplines, these examples include issues of concern in biological and social sciences as well as the humanities.



Using Multivariate Statistics

Using Multivariate Statistics Author CTI Reviews
ISBN-10 9781497091924
Release 2016-09-24
Pages 108
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Facts101 is your complete guide to Using Multivariate Statistics. In this book, you will learn topics such as Review of Univariate and Bivariate Statistics, Screening Date Priod to Analysis, Multiple Regression, and Analysis of Covariance plus much more. With key features such as key terms, people and places, Facts101 gives you all the information you need to prepare for your next exam. Our practice tests are specific to the textbook and we have designed tools to make the most of your limited study time.



Advanced and Multivariate Statistical Methods

Advanced and Multivariate Statistical Methods Author Craig A. Mertler
ISBN-10 9781351971669
Release 2016-10-24
Pages 390
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Ideal for non-math majors, Advanced and Multivariate Statistical Methods teaches students to interpret, present, and write up results for each statistical technique without overemphasizing advanced math. This highly applied approach covers the why, what, when and how of advanced and multivariate statistics in a way that is neither too technical nor too mathematical. Students also learn how to compute each technique using SPSS software. New to the Sixth Edition Instructor ancillaries are now available with the sixth edition. All SPSS directions and screenshots have been updated to Version 23 of the software. Student learning objectives have been added as a means for students to target their learning and for instructors to focus their instruction. Key words are reviewed and reinforced in the end of chapter material to ensure that students understand the vocabulary of advanced and multivariate statistics.



Applied Multivariate Analysis

Applied Multivariate Analysis Author S. James Press
ISBN-10 9780486442365
Release 2005-06-28
Pages 671
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Includes practical elements of matrix theory, continuous multivariate distributions and basic multivariate statistics in the normal distribution; regression and the analysis of variance; factor analysis and latent structure analysis; canonical correlations; stable portfolio analysis; classifications and discrimination models; control in the multivariate linear model; and structuring multivariate populations. 1982 edition.



Exploratory Multivariate Analysis by Example Using R Second Edition

Exploratory Multivariate Analysis by Example Using R  Second Edition Author Francois Husson
ISBN-10 9781315301860
Release 2017-05-08
Pages 262
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Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R, Second Edition focuses on four fundamental methods of multivariate exploratory data analysis that are most suitable for applications. It covers principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, and hierarchical cluster analysis. The authors take a geometric point of view that provides a unified vision for exploring multivariate data tables. Within this framework, they present the principles, indicators, and ways of representing and visualising objects that are common to the exploratory methods. The authors show how to use categorical variables in a PCA context in which variables are quantitative, how to handle more than two categorical variables in a CA context in which there are originally two variables, and how to add quantitative variables in an MCA context in which variables are categorical. They also illustrate the methods using examples from various fields, with related R code accessible in the FactoMineR package developed by the authors. The book has been written using minimal mathematics so as to appeal to applied statisticians, as well as researchers from various disciplines, including medical research and the social sciences. Readers can use the theory, examples, and software presented in this book in order to be fully equipped to tackle real-life multivariate data.



Applied Statistics

Applied Statistics Author Rebecca M. Warner
ISBN-10 9781483305974
Release 2012-04-10
Pages 1208
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Rebecca M. Warner's Applied Statistics: From Bivariate Through Multivariate Techniques, Second Edition provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked to think about the meaning of equations. Each chapter presents a complete empirical research example to illustrate the application of a specific method. Although SPSS examples are used throughout the book, the conceptual material will be helpful for users of different programs. Each chapter has a glossary and comprehension questions.



Applied Multivariate Statistics with SAS Software Second Edition

Applied Multivariate Statistics with SAS Software  Second Edition Author Ravindra Khattree
ISBN-10 1590476395
Release 2000-02-03
Pages 368
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The authors' approach to the information aids professors, researchers, and students in a variety of disciplines and industries. Extensive SAS code and the corresponding output accompany sample problems, and clear explanations of the various SAS procedures are included. Emphasis is on correct interpretation of the output to draw meaningful conclusions. Featuring both the theoretical and the practical, topics covered include multivariate analysis of experimental data and repeated measures data, graphical representation of data including biplots, and multivariate regression. In addition, a quick introduction to the IML procedure with special reference to multivariate data is available in an appendix. SAS programs and output integrated with the text make it easy to read and follow the examples. High-resolution graphs have been used in this new edition.



Applied Morphometry and Watershed Management Using RS GIS and Multivariate Statistics Case Studies

Applied Morphometry and Watershed Management Using RS  GIS and Multivariate Statistics Case Studies Author Yahya Farhan
ISBN-10 9781618964106
Release 2017-11-24
Pages 488
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“Applied Morphometry and Watershed Management” book is designed to introduce the recent developments related to applied morphometric studies of drainage basins. Applications of drainage basin morphometric analysis cover several topics of research such as: 1) Prioritization of sub-watersheds for soil and water conservation; 2) Surface water harvesting; 3) Assessment of groundwater potential and predicting of groundwater movement; 4) Geo-hazard assessment (i.e., soil erosion and sediment yield modeling, landslide susceptibility mapping; flashflood hazard and flood management; 5) The impact of Quaternary tectonics on structure and drainage network distortions.



Multivariate Statistics for Wildlife and Ecology Research

Multivariate Statistics for Wildlife and Ecology Research Author Kevin McGarigal
ISBN-10 9781461212881
Release 2013-12-01
Pages 283
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With its focus on the practical application of the techniques of multivariate statistics, this book shapes the powerful tools of statistics for the specific needs of ecologists and makes statistics more applicable to their course of study. It gives readers a solid conceptual understanding of the role of multivariate statistics in ecological applications and the relationships among various techniques, while avoiding detailed mathematics and the underlying theory. More importantly, the reader will gain insight into the type of research questions best handled by each technique and the important considerations in applying them. Whether used as a textbook for specialised courses or as a supplement to general statistics texts, the book emphasises those techniques that students of ecology and natural resources most need to understand and employ in their research. While targeted for upper-division and graduate students in wildlife biology, forestry, and ecology, and for professional wildlife scientists and natural resource managers, this book will also be valuable to researchers in any of the biological sciences.



Using R With Multivariate Statistics

Using R With Multivariate Statistics Author Randall E. Schumacker
ISBN-10 9781483377971
Release 2015-07-06
Pages 408
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Using R with Multivariate Statistics by Randall E. Schumacker is a quick guide to using R, free-access software available for Windows and Mac operating systems that allows users to customize statistical analysis. Designed to serve as a companion to a more comprehensive text on multivariate statistics, this book helps students and researchers in the social and behavioral sciences get up to speed with using R. It provides data analysis examples, R code, computer output, and explanation of results for every multivariate statistical application included. In addition, R code for some of the data set examples used in more comprehensive texts is included, so students can run examples in R and compare results to those obtained using SAS, SPSS, or STATA. A unique feature of the book is the photographs and biographies of famous persons in the field of multivariate statistics.



Introduction to Multivariate Statistical Analysis in Chemometrics

Introduction to Multivariate Statistical Analysis in Chemometrics Author Kurt Varmuza
ISBN-10 1420059491
Release 2016-04-19
Pages 336
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Using formal descriptions, graphical illustrations, practical examples, and R software tools, Introduction to Multivariate Statistical Analysis in Chemometrics presents simple yet thorough explanations of the most important multivariate statistical methods for analyzing chemical data. It includes discussions of various statistical methods, such as principal component analysis, regression analysis, classification methods, and clustering. Written by a chemometrician and a statistician, the book reflects the practical approach of chemometrics and the more formally oriented one of statistics. To enable a better understanding of the statistical methods, the authors apply them to real data examples from chemistry. They also examine results of the different methods, comparing traditional approaches with their robust counterparts. In addition, the authors use the freely available R package to implement methods, encouraging readers to go through the examples and adapt the procedures to their own problems. Focusing on the practicality of the methods and the validity of the results, this book offers concise mathematical descriptions of many multivariate methods and employs graphical schemes to visualize key concepts. It effectively imparts a basic understanding of how to apply statistical methods to multivariate scientific data.



Using Multivariate Statistics

Using Multivariate Statistics Author Addison-Wesley Longman, Incorporated
ISBN-10 0321049896
Release 2000-01-01
Pages
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Using Multivariate Statistics has been writing in one form or another for most of life. You can find so many inspiration from Using Multivariate Statistics also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Using Multivariate Statistics book for free.