This book enables readers who may not be familiar with matrices to understand a variety of multivariate analysis procedures in matrix forms. Another feature of the book is that it emphasizes what mode
Accessible and concise, with minimal mathematics, this fourth edition of a classic textbook on multivariate statistics is perfect as an introduction to the subject for non-statisticians. It covers all
Emphasizing conceptual understanding over mathematics, this user-friendly text introduces linear regression analysis to students and researchers across the social, behavioral, consumer, and health sci
A textbook on the use of advanced statistical methods in healthcare sciencesPrimer of Applied Regression & Analysis of Variance is a textbook especially created for medical, public health, and
Regression analysis is the primary technique that researchers in the social sciences use to analyze quantitative data. This statistical method is the subject of the second semester statistics course i
This book reviews the three most popular methods (and their extensions) in applied economics and other social sciences: matching, regression discontinuity, and difference in differences. The book intr
This book reviews the three most popular methods (and their extensions) in applied economics and other social sciences: matching, regression discontinuity, and difference in differences. The book intr
This book presents a comprehensive study of multivariate time series with linear state space structure. The emphasis is put on both the clarity of the theoretical concepts and on efficient algorithms
Like many people, Mui is having trouble learning regression analysis-or even staying awake in class. But with new motivation, in the form of a handsome but shy customer, and the help of her brilliant
This book creates a balance between the theory, practical applications, and computer implementation behind Regression—one of the most widely used techniques in analyzing and solving real world problem
Many parametric approaches to ranking multivariate populations have drawbacks in areas, such as business and industrial research. This book introduces a novel permutation-based nonparametric approach
Statistics with JMP: Hypothesis Tests, ANOVA and Regression Peter Goos, University of Leuven and University of Antwerp, Belgium David Meintrup, University of Applied Sciences Ingolstadt, Ger
This book discusses a class of Reduced Constructions which exhibit both mono- and bi-clausal characteristics. In Spanish, as well as other Romance languages, the most salient mono-clausal characterist
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 stat
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 stat
This book provides the limit theorems that can be used in the development of nonlinear cointegrating regression. The topics include weak convergence to a local time process, weak convergence to a mixt
Written by leading experts in the field, this edited volume brings together the latest findings in the area of nonparametric, robust and multivariate statistical methods. The individual contributions
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 statistic
Updates to this new edition include: more coverage of regression assumptions and model fit; additional material on residual analysis; more examples of transformations; and the inclusion of the measure
A traditional approach to developing multivariate statistical theory is algebraic. Sets of observations are represented by matrices, linear combinations are formed from these matrices by multiplying t
Combining a modern, data-analytic perspective with a focus on applications in the social sciences, theThird Edition of Applied Regression Analysis and Generalized Linear Modelsprovides in-depth covera
Clarifies modern data analysis through nonparametric density estimation for a complete working knowledge of the theory and methodsFeaturing a thoroughly revised presentation, Multivariate Density Esti
"This book provides graduate students in the social sciences with the basic skills that they need in order to estimate, interpret, present, and publish basic regression models using contemporary stand
"This book provides graduate students in the social sciences with the basic skills that they need in order to estimate, interpret, present, and publish basic regression models using contemporary stand
A basic understanding of multiple regression is helpful in carrying out good business practices—specifically in the areas of demand management and data analysis. This book on correlation and regressio
This unique book explains how to fashion useful regression models from commonly available data to erect models essential for evidence-based road safety management and research. Composed from technique
This book provides a view of low-rank and sparse computing, especially approximation, recovery, representation, scaling, coding, embedding and learning among unconstrained visual data. The book includ
This book summarizes the results of various models under normal theory with a brief review of the literature. Statistical Inference for Models with Multivariate t-Distributed Errors:Includes a wide ar
Experiments in Reduced Gravity: Sediment Settling on Mars is the first book to be published that reflects experiments conducted on Martian geomorphology in reduced gravity. This brief yet important bo
"Multivariate techniques are used to analyze data that arise from more than one variable in which there are relationships between the variables. Mainly based on the linearity of observed variables, th
The authors present tools and concepts of multivariate data analysis by means of exercises and their solutions. The first part is devoted to graphical techniques. The second part deals with multivaria
By focusing on underlying themes, this book helps readers better understand the connections between multivariate methods. For each method the author highlights: the similarities and differences betwee
By focusing on underlying themes, this book helps readers better understand the connections between multivariate methods. For each method the author highlights: the similarities and differences betwee
Drawing on the authors’ substantial expertise in modeling longitudinal and clustered data, this book presents a comprehensive treatment of quasi-least squares (QLS) regression—a computational approach
Since most datasets contain a number of variables, multivariate methods are helpful in answering a variety of research questions. Accessible to students and researchers without a substantial backgroun
This unique reference offers a balance between methodology and application, illustrating how and why to use quantile regression in a variety of areas such as economics, finance and computing. It prese
Regression Methods for Medical Research provides medical researchers with the skills they need to critically read and interpret research using more advanced statistical methods. The statistical requir
This new four-volume major work presents a collection of landmark studies on the topic of regression modeling, identifying the most important, fundamental articles out of thousands of relevant contrib
This bestseller will help you learn regression-analysis methods that you can apply to real-life problems. It highlights the role of the computer in contemporary statistics with numerous printouts and
