Practical Data Processing and Analysis Using R

Data mining is the art and science of intelligent data analysis. By building knowledge from information, data mining adds considerable value to the ever increasing stores of electronic data that aboun

A Practical Guide to Race Car Data Analysis was written for the amateur and lower-level professional racers who either have a data system in their cars or who may be thinking about installing one but

Models and methods for operational risks assessment and mitigation are gaining importance in financial institutions, healthcare organizations, industry, businesses and organisations in general. This

The second edition of this textbook concentrates on the practical applications of signal processing and is intended for upper division engineering and computer science students as well as professional

R, a free and open source program, is one of the most powerful and the fastest-growing statistics program. Microsoft Excel is the most widely used spreadsheet program, but many statisticians consider

Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining by Glenn J. Myatt (978-0-470-07471-8) and Making Sense of Data II: A Practical Guide to Data Visualization, Advance

In a way that is refreshingly engaging and readable, Daniel B. Wright and Kamala London describe the most useful of these techniques and provide step-by-step instructions, using the freeware R, to an

Ecological Models and Data in R is the first truly practical introduction to modern statistical methods for ecology. In step-by-step detail, the book teaches ecology graduate students and researchers

Successful statistical analysis of research data is an integral part of any social sciences degree. This straightforward and accessible text provides students with both a beginners guide and a continu

Although traditional texts present isolated algorithms and data structures, they do not provide a unifying structure and offer little guidance on how to appropriately select among them. Furthermore, t

This thoroughly revised and expanded third edition is a practical guide to data analysis using the bootstrap, cross-validation, and permutation tests. Only requiring minimal mathematics beyond algebra

The MINITAB lab manual is designed to be used with any Elementary Statistics textbook. The lessons are self-explanatory and explore topics that are covered in all elementary texts. The purpose in writ

Written for students, remote sensing specialists, researchers and SAR system designers, Processing of SAR Data shows how to produce quality SAR images. In particular, this practical reference presents

In this book the most important techniques available for longitudinal data analysis are discussed, including simple techniques such as the paired t-test and summary statistics, and more sophisticated

Spreadsheet skills are important for a first job, and DATA ANALYSIS USING MICROSOFT EXCEL prepares students to enter the world of work with stronger spreadsheet skills. Designed as a supplement to a m

Many statistical modelling and data analysis techniques can be difficult to grasp and apply, and it is often necessary to use computer software to aid the implementation of large data sets and to obta

Fully updated and expanded-a solid foundation for understanding experimental enzymology. This practical, up-to-date survey is designed for a broad spectrum of biological and chemical scientists who a

Powerful techniques have been developed in recent years for the analysis of digital data, especially the manipulation of images. This book provides an in-depth introduction to a range of these innovative, avante-garde data-processing techniques. It develops the reader's understanding of each technique and then shows with practical examples how they can be applied to improve the skills of graduate students and researchers in astronomy, electrical engineering, physics, geophysics and medical imaging. What sets this book apart from others on the subject is the complementary blend of theory and practical application. Throughout, it is copiously illustrated with real-world examples from astronomy, electrical engineering, remote sensing and medicine. It also shows how many, more traditional, methods can be enhanced by incorporating the new wavelet and multiscale methods into the processing. For graduate students and researchers already experienced in image processing and data analysis, this

This comprehensive workbook offers a thorough review of today's high performance plastics and manufacturing processes. Focusing on common processing problems and practical solutions this book surveys

This easy-to-understand introduction emphasizes the areas of probability theory and statistics that are important in environmental monitoring, data analysis, research, environmental field surveys, and

Two mainstreams intermingle in this treatment of practical statistics: (a) a sequence of philosophical attitudes the student needs for effective data analysis, and (b) a flow of useful and adaptable t

This 5th edition of this popular graduate textbook, presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. It includes numerous examples using nontrivial data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and monitoring a nuclear test ban treaty. The R package 'astsa' has had major updates and the text will reflect those updates. In general, the graphics have been improved. New topics include random number generation, modeling and fitting predator-prey interactions, more emphasis on structural models, testing for linearity, discussion of EM algorithm is more extensive, Bayesian analysis of state space models and MCMC is more extensive (including new scripts in astsa), particle methods are introduced, stochastic volatility coverage is expanded, changepoint detection is introduced (new topic).The