Assuming no knowledge of programming, this book presents both programming concepts and MATLAB’s built-in functions, providing a perfect platform for exploiting MATLAB’s extensive capabilities for tackling engineering problems. It starts with programming concepts such as variables, assignments, input/output, and selection statements, moves onto loops and then solves problems using both the ‘programming concept’ and the ‘power of MATLAB’ side-by-side. In-depth coverage is given to input/output, a topic that is fundamental to many engineering applications. Ancillaries available with the text: Instructor solution manual (available Aug. 1st) electronic images from the text (available Aug 16th) m-files (available Aug 1st) * Presents programming concepts and MATLAB built-in functions side-by-side, giving students the ability to program efficiently and exploit the power of MATLAB to solve problems. * In depth coverage of file input/output, a topic essential for many engineering applications * Systematic, step-by-step approach, building on concepts throughout the book, facilitating easier learning * Sections on ‘common pitfalls’ and ‘programming guidelines’ direct students towards best practice * New to this edition: More engineering applications help the reader learn Matlab in the context of solving technical problems New and revised end of chapter problems Stronger coverage of loops and vectorizing in a new chapter, chapter 5 Updated to reflect current features and functions of the current release of Matlab

R in Action is the first book to present both the R system and the use cases that make it such a compelling package for business developers. The book begins by introducing the R language, including the development environment. Focusing on practical solutions, the book also offers a crash course in practical statistics and covers elegant methods for dealing with messy and incomplete data using features of R. About the Technology 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 modules and utilities. This makes R a great way to get meaningful information from mountains of raw data. About the Book R in Action is a language tutorial focused on practical problems. It presents useful statistics examples and includes elegant methods for handling messy, incomplete, and nonnormal data that are difficult to analyze using traditional methods. And statistical analysis is only part of the story. You'll also master R's extensive graphical capabilities for exploring and presenting data visually. What's Inside Practical data analysis, step by step Interfacing R with other software Using R to visualize data Over 130 graphs Eight reference appendixes About the Reader About the Author Dr. Rob Kabacoff is a seasoned researcher who specializes in data analysis. He has taught graduate courses in statistical programming and manages the Quick-R website at statmethods.net. Quotes Lucid and engaging...and fun way to learn R! - Amos A. Folarin, University College London Finally, a book that brings R to the real world. - Charles Malpas, University of Melbourne R from a programmer's point of view. - Philipp K. Janert, Principal Value, LLC A great balance of targeted tutorials and in-depth examples. - Landon Cox, 360VL, Inc. An excellent introduction and reference from the author of the best R website. - Christopher Williams, University of Idaho

For the engineering and scientific professional, A Physicist’s Guide to Mathematica, Second Edition provides an updated reference guide based on the 2007 new 6.0 release, providing an organized and integrated desk reference with step-by-step instructions for the most commonly used features of the software as it applies to research in physics. For professors teaching physics and other science courses using the Mathematica software, A Physicist’s Guide to Mathematica, Second Edition is the only fully compatible (new software release) Mathematica text that engages students by providing complete topic coverage, new applications, exercises and examples that enable the user to solve a wide range of physics problems. Does not require prior knowledge of Mathematica or computer programming Can be used as either a primary or supplemental text for upper-division physics majors Provides over 450 end-of-section exercises and end-of-chapter problems Serves as a reference suitable for chemists, physical scientists, and engineers Compatible with Mathematica Version 6, a recent major release

Building on the unique features that made the first edition a bestseller, this second edition includes additional solved problems and web access to the large collection of MATLAB scripts that are highlighted throughout the text. The book offers expanded coverage of audio engineering, transducers, and sensor networking technology. It also includes new chapters on digital audio processing, as well as acoustics and vibrations transducers. The text addresses the use of meta-data architectures using XML and agent-based automated data mining and control. The numerous algorithms presented can be applied locally or network-based to solve complex detection problems.

MATLAB® in bioscience and biotechnology presents an introductory Matlab course oriented towards various collaborative areas of biotechnology and bioscience. It concentrates on Matlab fundamentals and gives examples of its application to a wide range of current bioengineering problems in computational biology, molecular biology, bio-kinetics, biomedicine, bioinformatics, and biotechnology. In the last decade Matlab has been presented to students as the first computer program they learn. Consequently, many non-programmer students, engineers and scientists have come to regard it as user-friendly and highly convenient in solving their specific problems. Numerous books are available on programming in Matlab for engineers in general, irrespective of their specialization, or for those specializing in some specific area, but none have been designed especially for such a wide, interdisciplinary, and topical area as bioengineering. Thus, in this book, Matlab is presented with examples and applications to various school-level and advanced bioengineering problems - from growing populations of microorganisms and population dynamics, reaction kinetics and reagent concentrations, predator-prey models, mass-transfer and flow problems, to sequence analysis and sequence statistics. This is the first book intended as a manual introducing biologists and other biotechnology engineers to work with Matlab It is suitable for beginners and inexperienced users; however, applications of Matlab to advanced problems such as the Monte Carlo method, curve fitting, and reliable machine diagnostics make the book relevant to university teachers as well The book is different in that it assumes a modest mathematical background for the reader and introduces the mathematical or technical concepts with a somewhat traditional approach; Matlab is then used as a tool for subsequent computer solution

Presents inference and simulation of stochastic process in the field of model calibration for financial times series modelled by continuous time processes and numerical option pricing. Introduces the bases of probability theory and goes on to explain how to model financial times series with continuous models, how to calibrate them from discrete data and further covers option pricing with one or more underlying assets based on these models. Analysis and implementation of models goes beyond the standard Black and Scholes framework and includes Markov switching models, Lévy models and other models with jumps (e.g. the telegraph process); Topics other than option pricing include: volatility and covariation estimation, change point analysis, asymptotic expansion and classification of financial time series from a statistical viewpoint. The book features problems with solutions and examples. All the examples and R code are available as an additional R package, therefore all the examples can be reproduced.

Maintaining its accessible approach to circuit analysis, the tenth edition includes even more features to engage and motivate engineers. Exciting chapter openers and accompanying photos are included to enhance visual learning. The book introduces figures with color-coding to significantly improve comprehension. New problems and expanded application examples in PSPICE, MATLAB, and LabView are included. New quizzes are also added to help engineers reinforce the key concepts.

With more than 200 practical recipes, this book helps you perform data analysis with R quickly and efficiently. The R language provides everything you need to do statistical work, but its structure can be difficult to master. This collection of concise, task-oriented recipes makes you productive with R immediately, with solutions ranging from basic tasks to input and output, general statistics, graphics, and linear regression. Each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an experienced data programmer, it will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process. Create vectors, handle variables, and perform other basic functions Input and output data Tackle data structures such as matrices, lists, factors, and data frames Work with probability, probability distributions, and random variables Calculate statistics and confidence intervals, and perform statistical tests Create a variety of graphic displays Build statistical models with linear regressions and analysis of variance (ANOVA) Explore advanced statistical techniques, such as finding clusters in your data "Wonderfully readable, R Cookbook serves not only as a solutions manual of sorts, but as a truly enjoyable way to explore the R language—one practical example at a time."—Jeffrey Ryan, software consultant and R package author

How do you use R to import, manage, visualize, and analyze real-world data? With this short, hands-on tutorial, you learn how to collect online data, massage it into a reasonable form, and work with it using R facilities to interact with web servers, parse HTML and XML, and more. Rather than use canned sample data, you'll plot and analyze current home foreclosure auctions in Philadelphia. This practical mashup exercise shows you how to access spatial data in several formats locally and over the Web to produce a map of home foreclosures. It's an excellent way to explore how the R environment works with R packages and performs statistical analysis. Parse messy data from public foreclosure auction postings Plot the data using R's PBSmapping package Import US Census data to add context to foreclosure data Use R's lattice and latticeExtra packages for data visualization Create multidimensional correlation graphs with the pairs() scatterplot matrix package

R is a powerful tool for statistics and graphics, but getting started with this language can be frustrating. This short, concise book provides beginners with a selection of how-to recipes to solve simple problems with R. Each solution gives you just what you need to know to use R for basic statistics, graphics, and regression. You'll find recipes on reading data files, creating data frames, computing basic statistics, testing means and correlations, creating a scatter plot, performing simple linear regression, and many more. These solutions were selected from O'Reilly's , which contains more than 200 recipes for R that you'll find useful once you move beyond the basics. R Cookbook

MATLAB: An Introduction with Applications 4th Edition walks readers through the ins and outs of this powerful software for technical computing. The first chapter describes basic features of the program and shows how to use it in simple arithmetic operations with scalars. The next two chapters focus on the topic of arrays (the basis of MATLAB), while the remaining text covers a wide range of other applications. MATLAB: An Introduction with Applications 4th Edition is presented gradually and in great detail, generously illustrated through computer screen shots and step-by-step tutorials, and applied in problems in mathematics, science, and engineering.

This new textbook in signals and systems provides a pedagogically rich approach to what can commonly be a mathematically dry subject. With features like historical notes, highlighted common mistakes, and applications in controls, communications, and signal processing, Chaparro helps students appreciate the usefulness of the techniques described in the book. Each chapter contains a section with MatLab applications. Pedagogically rich introduction to signals and systems using historical notes, pointing out "common mistakes", and relating concepts to realistic examples throughout to motivate learning the material Introduces both continuous and discrete systems early, then studies each (separately) in more depth later Extensive set of worked examples and homework assignments, with applications to controls, communications, and signal processing throughout Provides review of all the background math necessary to study the subject MatLab applications in every chapter

Visit the catalog page for Mathematica CookbookVisit the errata page for Mathematica Cookbook Mathematica Cookbook helps you master the application's core principles by walking you through real-world problems. Ideal for browsing, this book includes recipes for working with numerics, data structures, algebraic equations, calculus, and statistics. You'll also venture into exotic territory with recipes for data visualization using 2D and 3D graphic tools, image processing, and music. Although Mathematica 7 is a highly advanced computational platform, the recipes in this book make it accessible to everyone -- whether you're working on high school algebra, simple graphs, PhD-level computation, financial analysis, or advanced engineering models. Learn how to use Mathematica at a higher level with functional programming and pattern matching Delve into the rich library of functions for string and structured text manipulation Learn how to apply the tools to physics and engineering problems Draw on Mathematica's access to physics, chemistry, and biology data Get techniques for solving equations in computational finance Learn how to use Mathematica for sophisticated image processing Process music and audio as musical notes, analog waveforms, or digital sound samples

Why learn R? Because it's rapidly becoming the standard for developing statistical software. R in a Nutshell provides a quick and practical way to learn this increasingly popular open source language and environment. You'll not only learn how to program in R, but also how to find the right user-contributed R packages for statistical modeling, visualization, and bioinformatics. The author introduces you to the R environment, including the R graphical user interface and console, and takes you through the fundamentals of the object-oriented R language. Then, through a variety of practical examples from medicine, business, and sports, you'll learn how you can use this remarkable tool to solve your own data analysis problems. Understand the basics of the language, including the nature of R objects Learn how to write R functions and build your own packages Work with data through visualization, statistical analysis, and other methods Explore the wealth of packages contributed by the R community Become familiar with the lattice graphics package for high-level data visualization Learn about bioinformatics packages provided by Bioconductor "I am excited about this book. R in a Nutshell is a great introduction to R, as well as a comprehensive reference for using R in data analytics and visualization. Adler provides 'real world' examples, practical advice, and scripts, making it accessible to anyone working with data, not just professional statisticians."

The essential guide to MATLAB as a problem solving tool This text presents MATLAB both as a mathematical tool and a programming language, giving a concise and easy to master introduction to its potential and power. The fundamentals of MATLAB are illustrated throughout with many examples from a wide range of familiar scientific and engineering areas, as well as from everyday life. The new edition has been updated to include coverage of Symbolic Math and SIMULINK. It also adds new examples and applications, and uses the most recent release of Matlab.

Environmental Data Analysis with MatLab is for students and researchers working to analyze real data sets in the environmental sciences. One only has to consider the global warming debate to realize how critically important it is to be able to derive clear conclusions from often-noisy data drawn from a broad range of sources. This book teaches the basics of the underlying theory of data analysis, and then reinforces that knowledge with carefully chosen, realistic scenarios. MatLab, a commercial data processing environment, is used in these scenarios; significant content is devoted to teaching how it can be effectively used in an environmental data analysis setting. The book, though written in a self-contained way, is supplemented with data sets and MatLab scripts that can be used as a data analysis tutorial. Well written and outlines a clear learning path for researchers and students Uses real world environmental examples and case studies MatLab software for application in a readily-available software environment Homework problems help user follow up upon case studies with homework that expands them

This article demonstrates how the realworld data is imported, managed, visualized, and analyzed within the R statistical framework. Presented as a spatial mashup, this tutorial introduces the user to R packages, R syntax, and data structures. The user will learn how the R environment works with R packages as well as its own capabilities in statistical analysis. We will be accessing spatial data in several formats-html, xml, shapefiles, and text-locally and over the web to produce a map of home foreclosure auctions and perform statistical analysis on these events.

Bringing together all the relevant material to impart a clear understanding of how to analyze ROC curves, this book covers the fundamental theory as well as various special topics. It provides illustrative examples of the major methodological developments and includes as much of the mathematical theory as necessary without making the treatment too dense. The authors survey the uses made of the methodology across a range of different areas, from atmospheric science and geoscience to experimental psychology and sociology. They also list a number of websites from which software implementing the various techniques can be downloaded.

The first textbook of its kind, Quantitative Corpus Linguistics with R demonstrates how to use the open source programming language R for corpus linguistic analyses. Computational and corpus linguists doing corpus work will find that R provides an enormous range of functions that currently require several programs to achieve – searching and processing corpora, arranging and outputting the results of corpus searches, statistical evaluation, and graphing.

Written by a member of the R Development Core Team, this resource provides important information on how to work with research data. It contains a collection of diverse, computer-related topics, connecting them through numerous, real-world case studies. The author describes open source technologies and open standards and devotes separate chapters to each computer language, including HTML, XML, SQL, and R. Explanatory diagrams aid in understanding important concepts, helping readers perform research tasks with ease. In addition, the author's website includes a suite of exercises as well as the code and data sets used in the case studies.