Provides an introduction to MATLAB, teaching a sufficient subset of the functionality and giving practical experience on how to find more information. This book describes developments in MATLAB using realistic examples in order to prepare students for larger programming projects. It presents a large number of exercises, tips, and solutions.
Explains how to perform complex mathematical tasks with MATLAB[registered] programs. This book describes simple functions such as differentiation, integration, and plotting. It addresses advanced topics, including programming, producing executables, publishing results directly from MATLAB programs, and creating graphical user interfaces.
Presents programming concepts and MATLAB's built-in functions, providing a platform for exploiting MATLAB's extensive capabilities for tackling engineering problems. This book offers 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.
Presents both programming concepts and MATLAB's built-in functions, providing a platform for exploiting MATLAB's extensive capabilities for tackling engineering problems. This book offers coverage of file input/output, a topic essential for many engineering applications. It includes sections on 'common pitfalls' and 'programming guidelines'.
Due to its flexibility and availability, R has become the computing software of choice for statistical computing and generating graphics across various fields of research. This book offers a presentation of R, guiding new users through its many benefits, including the creation of high-quality graphics.
Provides detailed descriptions of both standard and advanced meta-analytic methods and their implementation in Stata. This book shows how to conduct and interpret meta-analyses as well as produce highly flexible graphical displays. Using meta-regression, it examines reasons for between-study variability in effect estimates.
R is a powerful and free software system for data analysis and graphics, with over 1, 200 add-on packages available. This book introduces R using SAS and SPSS terms. It demonstrates which of the add-on packages are most like SAS and SPSS and compares them to R's built-in functions.
R language is a powerful open source tool for data visualization and statistical computing - ideal as a replacement for statistical packages costing thousands of dollars. This book provides an overview of the language. It helps you learn how to use R to solve complex, real-world statistical problems and how to run R on your desktop.
Microsoft Excel is the most widely used spreadsheet program, but many statisticians consider its statistical tools too limited. In this book, the authors build on RExcel, an add-in for Excel. It is designed as a computational supplement to introductory statistics texts and provides RExcel examples covering the topics of the introductory course.
The fun and easy way to learn to use this leading business intelligence tool Written by an author team who is directly involved with SAS, this easy-to-follow guide is fully updated for the latest release of SAS and covers just what you need to put this popular software to work in your business.
Learn to become an R master! With R becoming one of the leading software packages, there is an increased need from new users, as well as experienced scientists and engineers to understand how to utilize the extensive capabilities of R software in any setting.
Offers an introduction to SAS statistical software, the premiere statistical data analysis tool for scientific research. This text presents SAS with step-by-step examples. It also presents data manipulation and statistical techniques, including a website with examples.
Using examples from a German longitudinal study, this title offers an introduction to Stata with an emphasis on data management, linear regression, logistic modeling, and using programs to automate repetitive tasks. It includes a discussion of Stata syntax and simple programming tools like foreach loops.
Assuming a knowledge only of basic calculus, matrix algebra, and elementary statistics, this book places emphasis on methods and the analysis of data sets. It covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, and also has an optional chapter on spectral analysis.
Written by researchers and developers behind the FEniCS Project, this book explores an advanced, expressive approach to the development of mathematical software. It also includes chapters that address fundamental aspects of the approach to automating the creation of finite element solvers.
Offers examples that illustrate programming concepts in the context of practical computational problems. This book presents an overview of computational statistics with an introduction to the R computing environment. It reviews basic concepts in probability and classical statistical inference.
Provides readers with step-by-step guidance on running a wide variety of statistical analyses in SPSS, Stata, and other programmes. This book covers charts and graphs through regression, time-series analysis, and factor analysis. It also provides a background of the method, explains how to run these tests in SPSS and Stata.
Offers an overview of the theory and application of linear and nonlinear mixed-effects models in the analysis of grouped data, such as longitudinal data, repeated measures, and multilevel data. This book presents a unified model-building strategy for both models and applies this to the analysis of over 20 real datasets from a various areas.
Parallel processing can be ideally suited for the solving of more complex problems in statistical computing. This book discusses code development in C++ and R, before going beyond to look at the valuable use of these two languages in unison. It requires a working knowledge of both the basic concepts in statistics and experience in programming.
Written by a highly experienced researcher and teachers, this book provides a much-needed guide to the proper use of Statistical Package for the Social Sciences (SPSS) software in social research, particularly where data may not be presented in the most convenient way.
Presents an introduction to MATLAB and its applications in engineering problem solving. This book covers the classical methods of electrical circuits, control systems, numerical methods, optimization, direct numerical integration methods, engineering mechanics and mechanical vibrations, using MATLAB software.
Sensor fusion deals with merging information from two or more sensors, where the area of statistical signal processing provides a powerful toolbox to attack both theoretical and practical problems. This book explains the theory and algorithms in statistical sensor fusion, covering estimation, detection and non-linear filtering theory.
Presents an array of methods applicable for reading data into R, and efficiently manipulating that data. This book covers the built-in functions, and a number of readily available packages from the Comprehensive R Archive Network. It provides guidelines for the effective use of programming constructs like.
SPSS is a sophisticated piece of software used by social scientists and related professionals for statistical analysis. This book is based on Version 16.0 of SPSS for Windows. It serves as a practical introduction to new users and also allows those wishing to undertake more advanced analysis to work their way systematically through each stage.
Covers major capabilities of MATLAB that are useful for beginning students. This book covers Function handles, Anonymous functions, and Subfunctions. It includes key applications such as plotting, programming, statistics and model building. It defines the terminology, syntax, and the use of the programming language.
Neuwirth and Arganbright (credentials not listed) offer an introduction to modeling a variety of applications with Microsoft Excel. The text features numerous tutorials and applications to illustrate the use of Excel in modeling and solving problems. Chapters focus on topics like dynamical models an
Suitable for engineers, computer scientists, and physicists, this book provides the reader with many applications, m-files, and practical examples to solve complex problems. It includes many short programs in MATLAB that can be used to solve problems involving systems of linear equations, matrices, vectors, computer graphics, and more.
Discusses exploratory data analysis (EDA) and how interactive graphical methods can help gain insights as well as generate new questions and hypotheses from datasets. This book summarizes principles and methodology, demonstrating how the different graphical representations of variables of a dataset are effectively used in an interactive setting.
For the engineering and scientific professional, this guide presents a reference guidance based on the 2007 new 6.0 Mathematica release, providing an organized and integrated desk reference with step by step instructions for the most often used features of the software as it applies to research in physics.
As the leading software application for symbolic mathematics, Mathematica is standard in many environments that rely on math, such as science, engineering, financial analysis, software development, and many other fields. This cookbook provides practical solutions on a wide range of topics for those who use this remarkable program.
Conquer the complexities of this open source statistical language R is fast becoming the de facto standard for statistical computing and analysis in science, business, engineering, and related fields. This book examines this complex language using simple statistical examples, showing how R operates in a user-friendly context.
If you have a TI-83 Plus graphing calculator, you have a veritable feast of features and functions at your fingertips, but chances are you don't take full advantage of them. This book helps you explore your TI-83 Plus Graphing Calculator. It also helps you to discover how your TI-83 Plus Graphing Calculator can solve various kinds of problems.
The updated guide to the newest graphing calculator from Texas Instruments The TI-Nspire graphing calculator is popular among high school and college students as a valuable tool for calculus, AP calculus, and college-level algebra courses. Its use is allowed on the major college entrance exams.
SPSS(R) 16.0: Advanced Statistical Procedures Companion contains valuable tips, warnings, and examples that will help you take advantage of SPSS and better analyze data. This book offers clear and concise explanations and examples of advanced statistical procedures in the SPSS Advanced and Regression modules.
This reference consists of core material for incorporating Maple and Mathematica as a working tool into different undergraduate mathematical courses, including algebra, geometry, calculus, complex functions, special functions and mathematical equations.
Serves as an introduction to the programming language, Java. Intended for scientists, engineers, and programmers, this book focuses on how Java, and object-oriented programming, can be used to solve science and engineering problems. It includes many examples from a number of different scientific and engineering areas.
Designed to help students analyze and interpret research data using IBM SPSS, this book shows readers how to choose the appropriate statistic based on the design, interpret output, and write about the results. It prepares readers for all of the steps in the research process, from design and data collection, to writing about the results.
Presents a collection of short articles - most of which having a review component - describing the developments of Nonparametric Statistics. This work includes topics such as: algorithic approaches; wavelets and nonlinear smoothers; graphical methods and data mining; biostatistics and bioinformatics; bagging and boosting; and more.
Offers a treatment of statistical topics and the intricacies of the R software. This book helps students master data manipulation and exploration. It treats exploratory data analysis with attention, includes a chapter on simulation, and provides an approach to linear models. It lays the foundation for study and development in statistics using R.
Explains the basics of S-PLUS. This book introduces important ideas of S-PLUS and R, its companion in implementing the S language. It takes the reader on a journey into the world of interactive computing, data exploration, and statistical analysis. It explains how to approach data sets and teach the corresponding S-PLUS commands.
Introduces the reader to data analysis with the most versatile statistical package: IBM SPSS Statistics 18. This book shows you how to describe and explore a data set with the help of SPSS' extensive graphics and data-handling menus. It warns you of the pitfalls arising from the misuse of statistics.
Shows second language researchers how to use the statistical program SPSS to conduct statistical tests frequently done in SLA research. This title also shows newcomers to both statistics and SPSS how to generate descriptive statistics, how to choose a statistical test, and how to conduct and interpret a variety of basic statistical tests.
Suitable for data analysts, this book demonstrates how to design and implement efficient workflows for both one-person projects and team projects. It describes planning, organizing, and documenting your work. It then introduces how to write and debug Stata do-files and how to use local and global macros.