Practical Data Processing and Analysis Using R

A practical guide to data mining using SQL and ExcelData Analysis Using SQL and Excel, 2nd Edition shows you how to leverage the two most popular tools for data query and analysis—SQL and Excel—to per

This greatly expanded 2nd edition provides a practical introduction to - data processing with Linux tools and the programming languages AWK and Perl- data management with the relational database syste

Through this book, researchers and students will learn to use R for analysis of large-scale genomic data and how to create routines to automate analytical steps. The philosophy behind the book is to s

See How Graphics Reveal InformationGraphical Data Analysis with R shows you what information you can gain from graphical displays. The book focuses on why you draw graphics to display data and which g

This is the second edition of the popular book on using R for statistical analysis and graphics. The authors, who run a popular blog supplementing their books, have focused on adding many new examples

Written for students and researchers in statistics and biostatistics, this book presents a modern introduction to categorical data analysis, with R integrated into the text as a data analysis method a

Characterized by the diversity of their applications, contingency tables play a key role in fields such as education and the social sciences. This volume presents a variety of new and sophisticated mo

R is a powerful language for statistical computing and graphics that can handle virtually any data-crunching task. It runs on all important platforms and provides thousands of useful specialized modu

This modern introduction to seismic data processing in both exploration and global geophysics demonstrates practical applications through real data and tutorial examples. The underlying physics and mathematics of the various seismic analysis methods are presented, giving students an appreciation of their limitations and potential for creating models of the sub-surface. Designed for a one-semester course, this textbook discusses key techniques within the context of the world's ever increasing need for petroleum and mineral resources - equipping upper undergraduate and graduate students with the tools they need for a career in industry. Examples presented throughout the text allow students to compare different methods and can be demonstrated using the instructor's software of choice. Exercises at the end of sections enable students to check their understanding and put the theory into practice and are complemented by solutions for instructors and additional case study examples online to c

Accessible to quantitative psychology researchers, this book introduces growth curve analysis (GCA) methods for applications in the behavioral sciences. It introduces the challenges involved with this

R is a popular programming language that statisticians use to perform a variety of statistical computing tasks. Rooted in Gregg Hartvigsen's extensive experience teaching biology, this text is an enga

R is a popular programming language that statisticians use to perform a variety of statistical computing tasks. Rooted in Gregg Hartvigsen's extensive experience teaching biology, this text is an enga

"This book prepares readers to analyze data and interpret statistical results using R more quickly than other texts. R is a challenging program to learn because code must be created to get started. To

"Panel Data Analysis using EViews provides graduate students, researchers, and statisticians with step-by-step guidance on how to apply EViews software to panel data analysis using appropriate empiric

"This book prepares readers to analyze data and interpret statistical results using R more quickly than other texts. R is a challenging program to learn because code must be created to get started. To

Practical Data Analysis is a practical, step-by-step guide to empower small businesses to manage and analyze your data and extract valuable information from the data. This book is for developers, smal

Meyers (psychology, California State U.-Sacramento), Gamst (psychology, U. of La Verne, California), and Guarino (biostatistics, Massachusetts General Hospital) introduce the commercial statistics pac

Applied Spatial Data Analysis with R, second edition, is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of intere

Practical statistics is a powerful tool used frequently by agricultural researchers and graduate students involved in investigating experimental design and analysis. One of the most widely used statis

Bridging the gap between introductory theory and practical knowledge, this second edition reflects the fast-moving field of DNA microarrays by adding new and updated chapters that cover cutting-edge m

In its revised and extended second edition, this book covers the basics of bioinformatics/information technology: programming with Bash, Sed and AWK, and the respective terminology. Case studies, exer

Data Analysis Using Stata, Third Edition is a comprehensive introduction to both statistical methods and Stata. Beginners will learn the logic of data analysis and interpretation and easily become sel

Statisticians and researchers will find Categorical Data Analysis Using SAS, Third Edition, by Maura Stokes, Charles Davis, and Gary Koch, to be a useful discussion of categorical data analysis techni

Assuming no prior knowledge of R, Spatial Data Analysis in Ecology and Agriculture Using R provides practical instruction on the use of the R programming language to analyze spatial data arising from

This volume on research technologies in the behavioral sciences provides graduate level students and researchers with detailed information on the development of robust longitudinal analysis tools usin

Addressing the problem of analysis of questionnaire data and interpretation of results, this book proposes a methodology that uses R software. The author takes a practical approach to the subject, pre

"The book provides a practical introduction to the most important topics in image and video processing using MATLAB (and its Image Processing Toolbox) as a tool to demonstrate the most important techn

Richly illustrated in color, Statistics and Data Analysis for Microarrays Using R and Bioconductor, Second Edition provides a clear and rigorous description of powerful analysis techniques and algorit

A practical guide to selecting and applying the most appropriate model for analysis of cross section data using EViews."This book is a reflection of the vast experience and knowledge of the author. It

Too often in biostatistical research and clinical trials, a knowledge gap exists between developed statistical methods and the applications of these methods. Filling this gap, Clinical Trial Data Anal

Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R focuses on four fundamental methods of multivariate exploratory data analysis that are most s

Information systems and intelligent knowledge processing are playing an increasing role in business, science and technology. Recently, advanced information systems have evolved to facilitate the co-e

Using R for Data Management, Statistical Analysis, and Graphics presents an easy way to learn how to perform an analytical task in R, without having to navigate through the extensive, idiosyncratic,

Taking a thematic approach to the use of Excel spreadsheets in introductory business data analysis, this text has been designed to explain the overall nature of what is to be achieved and also instru

Discover what you can do with R! Introducing the R system, covering standard regression methods, then tackling more advanced topics, this book guides users through the practical, powerful tools that the R system provides. The emphasis is on hands-on analysis, graphical display, and interpretation of data. The many worked examples, from real-world research, are accompanied by commentary on what is done and why. The companion website has code and datasets, allowing readers to reproduce all analyses, along with solutions to selected exercises and updates. Assuming basic statistical knowledge and some experience with data analysis (but not R), the book is ideal for research scientists, final-year undergraduate or graduate-level students of applied statistics, and practising statisticians. It is both for learning and for reference. This third edition expands upon topics such as Bayesian inference for regression, errors in variables, generalized linear mixed models, and random forests.

The advances of book history and editorial theory remind us that it is vital to look behind the text we read. Sukanta Chaudhuri explores, at a very fundamental level, how texts are constituted and ho

R — the statistical and graphical environment is rapidly emerging as an important set of teaching and research tools for biologists. This book draws upon the popularity and free availability of

R — the statistical and graphical environment is rapidly emerging as an important set of teaching and research tools for biologists. This book draws upon the popularity and free availability of R to c

Scientists often collect samples of curves and other functional observations, and develop models where parameters are also functions. This volume in the UseR! Series is aimed at a wide range of reade

An All-in-One Resource for Using SAS and R to Carry out Common TasksProvides a path between languages that is easier than reading complete documentationSAS and R: Data Management, Statistical Analysis