Showing results for "Contingency Table Analysis Methods and Implementation Using R Maria Kateri German"

Contingency tables arise in diverse fields, including life sciences, education, social and political sciences, notably market research and opinion surveys. Their analysis plays an essential role in gaining insight into structures of the quantities under consideration and in supporting decision making.Combining both theory and applications, this book presents models and methods for the analysis of two- and multidimensional-contingency tables. The author uses a threefold approach, pr...

The study of distributed algorithms provides the needed background in many real-life applications, such as: distributed real-time systems, wireless sensor networks, mobile ad hoc networks and distributed databases.The main goal of Guide to Distributed Algorithms is to provide a detailed study of the design and analysis methods of distributed algorithms and to supply the implementations of most of the presented algorithms in Python language, which is the unique feature of t...

This book is an overview of the Bayesian approach to applying the most important inferential methods of statistical science. It is designed as a textbook for advanced undergraduate and master’s students in Data Science, Statistics, or Mathematics who are interested in learning about Bayesian statistics.The reader should be familiar with calculus and should have taken a statistical inference Statistics course covering the basic rules of probability, probability distributions and exp...

Practical examples with real-world projects in GIS, Remote sensing, Geospatial data management and Analysis using the R programming languageKey FeaturesUnderstand the basics of R and QGIS to work with GIS and remote sensing dataLearn to manage, manipulate, and analyze spatial data using R and QGISApply machine learning algorithms to geospatial data using R and QGISBook DescriptionManaging spatial data has always been challeng...

Do you want to get better, become efficient, and find new opportunities with this SPSS statistical tool?If your answer is yes, then this book will answer your questions about the SPSS program. This Statistical Analytic Tool is widely used in several fields, such as competitor analysis, surveys, market research, doctoral or Ph.D. research, business administration, and more. It is a flexible and all-inclusive data management and analysis tool that will help you access better and more...

Students and research workers in mathematics, physics, engineering and other sciences will find this compilation invaluable. All the information included is practical, rarely used results are excluded. Great care has been taken to present all results concisely and clearly. Excellent to keep as a handy reference! If you don't have a lot of time but want to excel in class, this book helps you: Brush up before tests Find answers fast Learn key formulas and tables Study quickly and more effect...

Third-variable effect refers to the effect transmitted by third-variables that intervene in the relationship between an exposure and a response variable. Differentiating between the indirect effect of individual factors from multiple third-variables is a constant problem for modern researchers.Statistical Methods for Mediation, Confounding and Moderation Analysis Using R and SAS introduces general definitions of third-variable effects that are adaptable to...

This book provides a practice-oriented overview of the necessary prerequisites, the mode of operation, and the individual steps for the successful introduction of Robotic Process Automation (RPA). In addition to theoretical basics, practical examples from controlling and accounting illustrate the enormous potential of this technology....

This book provides a selection of modern and sophisticated methodologies for the analysis of large and complex univariate and multivariate categorical data. It gives an overview of a substantive and broad collection of topics in the analysis of categorical data, including association, marginal and graphical models, time series and fixed effects models, as well as modern methods of estimation such as regularization, Bayesian estimation and bias reduction methods, along with new simple measu...

Get Up to Speed on Many Types of Adaptive DesignsSince the publication of the first edition, there have been remarkable advances in the methodology and application of adaptive trials. Incorporating many of these new developments, Adaptive Design Theory and Implementation Using SAS and R, Second Edition offers a detailed framework to understand the

Foundations of Statistics for Data Scientists: With R and Python is designed as a textbook for a one- or two-term introduction to mathematical statistics for students training to become data scientists. It is an in-depth presentation of the topics in statistical science with which any data scientist should be familiar, including probability distributions, descriptive and inferential statistical methods, and linear modeling. The book assumes knowledge of basic calculus, so ...

Presented in a comprehensive manner, this book provides a comprehensive foundation in algebraic approaches for the analysis of different types of social networks such as multiple, signed, and affiliation networks. The study of such configurations corresponds to the structural analysis within the social sciences, and the methods applied for the analysis are in the areas of abstract algebra, combinatorics, and graph theory.Current research in social networks has moved toward the exam...