Ideal for courses on multivariate statistics found in psychology, education, sociology, and business departments, the book also appeals to practicing researchers with little or no training in multivariate methods. Working knowledge of matrix algebra is not assumed. Pituch Publisher: Routledge ISBN: Category: Psychology Page: View: Read Now » Now in its 6th edition, the authoritative textbook Applied Multivariate Statistics for the Social Sciences, continues to provide advanced students with a practical and conceptual understanding of statistical procedures through examples and data-sets from actual research studies.
Author : Susan R. Biometry is a broad discipline covering all applications of statistics and mathematics to biology. The Theme Biometrics is divided into areas of expertise essential for a proper application of statistical and mathematical methods to contemporary biological problems.
These volumes are aimed at the following five major target audiences: University and College students Educators, Professional practitioners, Research personnel and Policy analysts, managers, and decision makers and NGOs.
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. Author : Rangaraj M. As the scope and complexity of imaging technology steadily increase, more advanced techniques are required to solve the emerging challenges. Biomedical Image Analysis demonstr. Author : Theodore W. Broken down into three sections, this book has been structured to allow students in economics and finance to work their way through a well formulated exploration of this core topic.
The first part of this book is devoted to graphical techniques. The second deals with multivariate random variables and presents the derivation of estimators and tests for various practical situations. The final section contains a wide variety of exercises in applied multivariate data analysis. Author : Howard E. 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.
Author : Charles E. This book is intended to serve a broad scientific audience, but more specifi cally is geared toward scientists doing studies in geohydrology and related geo sciences. Some of the procedures are classical in scope but others are on the forefront of statistical science and have received limited use in geohydrology or related sciences. The past three decades have seen a significant jump in the application of new research methodologies that focus on analyzing large databases.
With more general applications being developed by statisticians in various disciplines, multivariate quantitative procedures are evolving for better scientific applica tion at a rapid rate and now provide for quick and informative analyses of large datasets. Relevant Courses. Multivariate Statistics Upper-Level Statistics.
Sign In We're sorry! Username Password Forgot your username or password? Sign Up Already have an access code? Instructor resource file download The work is protected by local and international copyright laws and is provided solely for the use of instructors in teaching their courses and assessing student learning.
Signed out You have successfully signed out and will be required to sign back in should you need to download more resources. For this new edition, the book has been updated and extensively revised and now includes an extended chapter on cluster analysis.
The Quantlet platform, quantlet. Its goal is to promote reproducibility and offer a platform for sharing validated knowledge native to the social web. QuantNet and the corresponding data-driven document-based visualization allow readers to reproduce the tables, pictures and calculations presented in this Springer book.
Matrix theory useful in multivariate analysis; Continuous multivariate distributions. Author : S. The normal distribution, Bayesian inference; Multivariate large sample distributions and approximations; The wishart and related distributions; Other continuous multivariate distributions; Basic multivariate statitics in the normal distribution; Regression and the analysis of variance; Principal components; Factor analysis and latent structure analysis; Canonical correlation; Stable portfolio analysis; Classification and discrimination models; Control in the multivariate linear model; Structuring multivariate populations multidimensional scaling and clustering.
Author : Brian Everitt Publisher: Springer ISBN: Category: Mathematics Page: View: Read Now » The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings are taken on each of the units in the data set. These units might be human subjects, archaeological artifacts, countries, or a vast variety of other things. In a few cases, it may be sensible to isolate each variable and study it separately, but in most instances all the variables need to be examined simultaneously in order to fully grasp the structure and key features of the data.
Multivariate analysis includes methods both for describing and exploring such data and for making formal inferences about them. The aim of all the techniques is, in general sense, to display or extract the signal in the data in the presence of noise and to find out what the data show us in the midst of their apparent chaos.
An Introduction to Applied Multivariate Analysis with R explores the correct application of these methods so as to extract as much information as possible from the data at hand, particularly as some type of graphical representation, via the R software.
Throughout the book, the authors give many examples of R code used to apply the multivariate techniques to multivariate data. Author : Richard A. Its primary goal is to impart the knowledge necessary to make proper interpretations and select appropriate techniques for analysing multivariate data. The full text downloaded to your computer With eBooks you can: search for key concepts, words and phrases make highlights and notes as you study share your notes with friends eBooks are downloaded to your computer and accessible either offline through the Bookshelf available as a free download , available online and also via the iPad and Android apps.
Upon purchase, you'll gain instant access to this eBook. Time limit The eBooks products do not have an expiry date. You will continue to access your digital ebook products whilst you have your Bookshelf installed. Author : James P. Helpful narrative and numerous examples enhance understanding and a chapter on matrix algebra serves as a review.
In addition to demonstrating how to use these packages, the author stresses the importance of checking the data, assessing the assumptions, and ensuring adequate sample size by providing guidelines so that the results can be generalized. The book is noted for its extensive applied coverage of MANOVA, its emphasis on statistical power, and numerous exercises including answers to half. Ideal for courses on multivariate statistics found in psychology, education, sociology, and business departments, the book also appeals to practicing researchers with little or no training in multivariate methods.
Working knowledge of matrix algebra is not assumed. Author : Paul E. Green Publisher: Academic Press ISBN: Category: Mathematics Page: View: Read Now » Mathematical Tools for Applied Multivariate Analysis provides information pertinent to the aspects of transformational geometry, matrix algebra, and the calculus that are most relevant for the study of multivariate analysis.
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