Practical Data Processing and Analysis Using R

This state-of-the-art account unifies material developed in journal articles over the last 35 years, with two central thrusts: It describes a broad class of system models that the authors call 'stochastic processing networks' (SPNs), which include queueing networks and bandwidth sharing networks as prominent special cases; and in that context it explains and illustrates a method for stability analysis based on fluid models. The central mathematical result is a theorem that can be paraphrased as follows: If the fluid model derived from an SPN is stable, then the SPN itself is stable. Two topics discussed in detail are (a) the derivation of fluid models by means of fluid limit analysis, and (b) stability analysis for fluid models using Lyapunov functions. With regard to applications, there are chapters devoted to max-weight and back-pressure control, proportionally fair resource allocation, data center operations, and flow management in packet networks. Geared toward researchers and grad

Responding to the developments of the past twenty years, Les Kirkup has thoroughly updated his popular book on experimental methods, while retaining the extensive coverage and practical advice from the first edition. Many topics from that edition remain, including keeping a record of work, how to deal with measurement uncertainties, understanding the statistical basis of data analysis and reporting the results of experiments. However, with new technologies influencing how experiments are devised, carried out, analyzed, presented and reported, this new edition reflects the digital changes which have taken place and the increased emphasis on the importance of communication skills in reporting results. Bringing together key elements of experimental methods into one coherent book, it is perfect for students seeking guidance with their experimental work, including how to acquire, analyse and present data. Exercises, worked examples and end-of-chapter problems are provided throughout the boo

With an emphasis on experimental design and sampling, The Analysis of Ecological Data Using R presents all of the necessary statistical methods along with the ecological background for each problem. E

Many consider Lewis Binford to be the single most influential figure in archaeology in the last half-century. His contributions to the "New Archaeology" changed the course of the field, as he argued f

Written for those who need an introduction, Applied Time Series Analysis reviews applications of the popular econometric analysis technique across disciplines. Carefully balancing accessibility with r

Spatial Data Analysis in Ecology and Agriculture Using R, 2nd Edition provides practical instruction on the use of the R programming language to analyze spatial data arising from research in ecology,

Understand the fundamental factors of data storage system performance and master an essential analytical skill using block trace via applications such as MATLAB and Python tools. You will increase you

Examine business problems and use a practical analytical approach to solve them by implementing predictive models and machine learning techniques using SAS and the R analytical language. This bo

This book provides a broad introduction to computational aspects of Singular Spectrum Analysis (SSA) which is a non-parametric technique and requires no prior assumptions such as stationarity, normali

This book provides a complete and modern guide to web scraping, using Python as the programming language, without glossing over important details or best practices. Written with a data science audie

This is a guide for anyone interested in practical astronomy but intimidated by the idea of investing in a telescope. It explores the world of remote observing, which requires nothing more than a lapt

"This book explores the extraction and prediction of patterns at multiple levels of abstraction. It involves a procedure handling both numeric and nominal data at once using a single method and the me

This new volume covers a selection of important novel technological interventions in dairy science, from the physical properties of milk and other milk products to non-thermal processing of milk. It a

This book provides a practical supplement to Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood, coauthored by the first author, which will publish in a second edition in

This is a solution-oriented book providing an end-to-end look at building Internet-of-Things solutions using the Microsoft Azure IoT Suite. You'll learn about data acquisition and analysis, even real-

This is the second edition of a practical book on exploratory multivariate analysis. It takes an example-driven approach, with lots of detailed examples using real data, all coded in R, with implement

This book is aimed at students in communications and signal processing who want to extend their skills in the energy area. It describes power systems and why these backgrounds are so useful to smart g

Is there more to qualitative data collection than face-to-face interviews? Answering with a resounding 'yes', this book introduces the reader to a wide array of exciting and novel techniques for collecting qualitative data in the social and health sciences. Collecting Qualitative Data offers a practical and accessible guide to textual, media and virtual methods currently under-utilised within qualitative research. Contributors from a range of disciplines share their experiences of implementing a particular technique, provide step-by-step guidance to using that approach, and highlight both the potential and pitfalls. From gathering blog data to the story completion method to conducting focus groups online, the methods and data types featured in this book are ideally suited to student projects and other time- and resource-limited research. In presenting several innovative ways that data can be collected, new modes of scholarship and new research orientations are opened up to student rese

Program for data analysis using R and learn practical skills to make your work more efficient. This book covers how to automate running code and the creation of reports to share your results, as well

With the powerful interactive and visual functionality of JMP, you can dynamically analyze market data to transform it into actionable and useful information with clear, concise, and insightful report

As neural data becomes increasingly complex, neuroscientists now require skills in computer programming, statistics, and data analysis. This book teaches practical neural

This book serves as a hands-on guide to the "acs" R package for demographers, planners, and other researchers who work with American Community Survey (ACS) data. It gathers the most common problems as

With this comprehensive and accessible introduction to the field, you will gain all the skills and knowledge needed to work with current and future audio, speech, and hearing processing technologies. Topics covered include mobile telephony, human-computer interfacing through speech, medical applications of speech and hearing technology, electronic music, audio compression and reproduction, big data audio systems and the analysis of sounds in the environment. All of this is supported by numerous practical illustrations, exercises, and hands-on MATLAB® examples on topics as diverse as psychoacoustics (including some auditory illusions), voice changers, speech compression, signal analysis and visualisation, stereo processing, low-frequency ultrasonic scanning, and machine learning techniques for big data. With its pragmatic and application driven focus, and concise explanations, this is an essential resource for anyone who wants to rapidly gain a practical understanding of speech and audi

Many problems in biology require an understanding of the relationships among variables in a multivariate causal context. Exploring such cause-effect relationships through a series of statistical methods, this book explains how to test causal hypotheses when randomised experiments cannot be performed. This completely revised and updated edition features detailed explanations for carrying out statistical methods using the popular and freely available R statistical language. Sections on d-sep tests, latent constructs that are common in biology, missing values, phylogenetic constraints, and multilevel models are also an important feature of this new edition. Written for biologists and using a minimum of statistical jargon, the concept of testing multivariate causal hypotheses using structural equations and path analysis is demystified. Assuming only a basic understanding of statistical analysis, this new edition is a valuable resource for both students and practising biologists.

Data Gathering, Analysis and Protection of Privacy through Randomized Response Techniques: Qualitative and Quantitative Human Traitstackles how to gather and analyze data relating to stigmatizing huma

This volume is an introduction to labor market indicator analysis and a guide for analyzing household survey data using the ADePT ILO Labor Market Indicators Module. The analytical framework and appro

The field's bestselling reference, updated with the latest tools, data, and techniquesCost-Effectiveness Analysis in Health is a practical introduction to the tools, methods, and procedures used world

Get the most out of your data by getting more out of TableauTableau Your Data! shows you how to build dynamic, best of breed visualizations using the Tableau Software toolset. This comprehensive guide