Practical Data Processing and Analysis Using R

Careful analysis of data is becoming more and more critical in business. Across large businesses such as Google, Netflix, and Amazon, large amounts of data are gathered on matters such as customer beh

Developed from the author’s graduate-level courses, the first edition of this book filled the need for a comprehensive, self-contained, and hands-on treatment of radar systems analysis and design. It

In biostatistical research and courses, practitioners and students often lack a thorough understanding of how to apply statistical methods to synthesize biomedical and clinical trial data. Filling thi

With a focus on presenting basic statistical concepts in a friendly and accessible style, this book focuses on the more subjective side of statistics—the art of data analysis. It provides fun, common

Guiding students through the task of doing computer-assisted analysis using NVivo, this fully-updated second edition helps readers with every step of the process using clear directions and plenty of s

Guiding students through the task of doing computer-assisted analysis using NVivo, this fully-updated second edition helps readers with every step of the process using clear directions and plenty of s

"Discover Novel and Insightful Knowledge from Data Represented as a GraphPractical Graph Mining with R presents a "do-it-yourself" approach to extracting interesting patterns from graph data. It cover

Gravity surveys have a huge range of applications, indicating density variations in the subsurface and identifying man-made structures, local changes of rock type or even deep-seated structures at the crust/mantle boundary. This important one-stop book combines an introductory manual of practical procedures with a full explanation of analysis techniques, enabling students, geophysicists, geologists and engineers to understand the methodology, applications and limitations of a gravity survey. Filled with examples from a wide variety of acquisition problems, the book instructs students in avoiding common mistakes and misconceptions. It explores the increasing near-surface geophysical applications being opened up by improvements in instrumentation and provides more advance-level material as a useful introduction to potential theory. This is a key text for graduate students of geophysics and for professionals using gravity surveys, from civil engineers and archaeologists to oil and mineral

Six Sigma statistical methodology using Minitab"Problem Solving and Data Analysis using Minitab "presents example-based learning to aid readers in understanding how to use MINITAB 16 for statistical a

This book covers the fundamental aspects of categorical data analysis with an emphasis on how to implement the models used in the book using SAS and SPSS. This is accomplished through the frequent use

This book introduces using R for data mining. Data mining techniques are widely used in government agencies, banks, insurance, retail, telecom, medicine and research. Recently, there is an increasing

A practical introduction to using Mplus for the analysis of multivariate data, this volume provides step-by-step guidance, complete with real data examples, numerous screen shots, and output excerpts.

?????The intensive use of automatic data acquisition system and the use of cloud computing for process monitoring have led to an increased occurrence of industrial processes that utilize statistical p

In this sequel to two earlier volumes, the authors now focus on the long-time behavior of evolution inclusions, based on the theory of extremal solutions to differential-operator problems. This approa

With an emphasis on social science applications, Event History Analysis with R presents an introduction to survival and event history analysis using real-life examples. Keeping mathematical details to

The ability to summarise data, compare models and apply computer-based analysis tools are vital skills necessary for studying and working in the physical sciences. This textbook supports undergraduate students as they develop and enhance these skills. Introducing data analysis techniques, this textbook pays particular attention to the internationally recognised guidelines for calculating and expressing measurement uncertainty. This new edition has been revised to incorporate Excel® 2010. It also provides a practical approach to fitting models to data using non-linear least squares, a powerful technique which can be applied to many types of model. Worked examples using actual experimental data help students understand how the calculations apply to real situations. Over 200 in-text exercises and end-of-chapter problems give students the opportunity to use the techniques themselves and gain confidence in applying them. Answers to the exercises and problems are given at the end of the book

This book is the definitive guide to cash flow statement analysis and forecasting. It takes the reader from an introduction about how cash flows move within a business, through to a detailed rev

A pragmatic approach to statistics, data analysis and decision modeling. Statistics, Data Analysis & Decision Modeling focuses on the practical understanding of its topics, allowing readers to d

Data Communication and Networking, First Edition provides a solid, thorough overview of data communications and networking for Engineering Technology programs. This text covers information for one or more courses spanning digital communication systems, computer communication and networks, and data communications. It is specifically written and designed for engineering and engineering technology learners by using a systematic and visual approach with abundant tables, illustrations, and practical examples making it easy for students to comprehend concepts. Content begins with data communication, signal conversion and issues in data transmission. Each chapter includes an introduction, summary of key information, as well as practice questions and problems with answers. The text also includes coverage of network and network standards, Ethernet, network components and Transmission Control and Internets Protocols (TCP/IP). The integration of applications and laboratory experiments are found t

Bayesian statistics has exploded into biology and its sub-disciplines, such as ecology, over the past decade. The free software program WinBUGS and its open-source sister OpenBugs is currently the onl

Resampling methods—techniques for repeatedly resampling data to obtain results—are being used in virtually every research area. This practical guide discusses the applications of these methods in a wi

Functional magnetic resonance imaging (fMRI) has become the most popular method for imaging brain function. Handbook of Functional MRI Data Analysis provides a comprehensive and practical introduction to the methods used for fMRI data analysis. Using minimal jargon, this book explains the concepts behind processing fMRI data, focusing on the techniques that are most commonly used in the field. This book provides background about the methods employed by common data analysis packages including FSL, SPM and AFNI. Some of the newest cutting-edge techniques, including pattern classification analysis, connectivity modeling and resting state network analysis, are also discussed. Readers of this book, whether newcomers to the field or experienced researchers, will obtain a deep and effective knowledge of how to employ fMRI analysis to ask scientific questions and become more sophisticated users of fMRI analysis software.

This book provides accessible treatment to state-of-the-art approaches to analyzing longitudinal studies. Comprehensive coverage of the most popular analysis tools allows readers to pick and choose th

All students taking laboratory courses within the physical sciences and engineering will benefit from this book, whilst researchers will find it an invaluable reference. This concise, practical guide brings the reader up-to-speed on the proper handling and presentation of scientific data and its inaccuracies. It covers all the vital topics with practical guidelines, computer programs (in Python), and recipes for handling experimental errors and reporting experimental data. In addition to the essentials, it also provides further background material for advanced readers who want to understand how the methods work. Plenty of examples, exercises and solutions are provided to aid and test understanding, whilst useful data, tables and formulas are compiled in a handy section for easy reference.

All students taking laboratory courses within the physical sciences and engineering will benefit from this book, whilst researchers will find it an invaluable reference. This concise, practical guide brings the reader up-to-speed on the proper handling and presentation of scientific data and its inaccuracies. It covers all the vital topics with practical guidelines, computer programs (in Python), and recipes for handling experimental errors and reporting experimental data. In addition to the essentials, it also provides further background material for advanced readers who want to understand how the methods work. Plenty of examples, exercises and solutions are provided to aid and test understanding, whilst useful data, tables and formulas are compiled in a handy section for easy reference.

INTRODUCTION TO STATISTICS AND DATA ANALYSIS, 4th Edition, introduces you to the study of statistics and data analysis by using real data and attention-grabbing examples. The authors guide you throug

Statistics: The Exploration and Analysis of Data, 7th Edition, introduces you to the study of statistics and data analysis by using real data and attention-grabbing examples. The authors guide you th

"From the First Edition...Exploratory data analysis (EDA) was conceived at a time when computers were not widely used, and thus computational ability was rather limited. As computational sophisticatio

Modern signal and image acquisition systems used in the field of cardiology acquire, analyze, and store data digitally. Surface electrocardiography, intra-cardiac electrogram recording, echocardiogra

This presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The authors demonstrate how to analyze data—showing code, grap

Humans are remarkable in processing speech, audio, image and some biomedical signals. Artificial neural networks are proved to be successful in performing several cognitive, industrial and scientific

Multimedia processing demands efficient programming. This book shows you how to optimize data, singal, image, audio, speech, and video processing algorithms on embedded processors for real-time media

The purpose of this book is to get a practical understanding of the most common processing techniques in earthquake seismology. The book deals with manual methods and computer assisted methods. Each t

Data Structures and Problem Solving Using Java takes a practical and unique approach to data structures that separates interface from implementation. It is suitable for the second or third programming

A Proven Guide for Easily Using R to Effectively Analyze DataLike its bestselling predecessor, A Handbook of Statistical Analyses Using R, Second Edition provides a guide to data analysis using the R

The first cutting-edge guide to using the SAS® system for the analysis of econometric data Applied Econometrics Using the SAS® System is the first book of its kind to treat the analysis

Providing reliable information on an intervention effect, meta-analysis is a powerful statistical tool for analyzing and combining results from individual studies. Meta-Analysis of Binary Data Using P

R is rapidly growing in popularity as the environment of choice for data analysis and graphics both in academia and industry. Lattice brings the proven design of Trellis graphics (originally develope

Humans are remarkable in processing speech, audio, image and some biomedical signals. Artificial neural networks are proved to be successful in performing several cognitive, industrial and scientific

Intended for anyone needing to apply statistical analysis to a large variety of science and engineering problems, this book shows how to use SPSS, MATLAB, STATISTICA and R for data description, statis