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Books > Computing & IT > Computer software packages > Other software packages
Statistics is made simple with this award-winning guide to using R and applied statistical methods. With a clear step-by-step approach explained using real world examples, learn the practical skills you need to use statistical methods in your research from an expert with over 30 years of teaching experience. With a wealth of hands-on exercises and online resources created by the author, practice your skills using the data sets and R scripts from the book with detailed screencasts that accompany each script. This book is ideal for anyone looking to: * Complete an introductory course in statistics * Prepare for more advanced statistical courses * Gain the transferable analytical skills needed to interpret research from across the social sciences * Learn the technical skills needed to present data visually * Acquire a basic competence in the use of R and RStudio. This edition also includes a gentle introduction to Bayesian methods integrated throughout. The author has created a wide range of online resources, including: over 90 R scripts, 36 datasets, 37 screen casts, complete solutions for all exercises, and 130 multiple-choice questions to test your knowledge.
Starting from a basic knowledge of mathematics and mechanics gained in standard foundation classes, "Theory of Lift: Introductory Computational Aerodynamics in MATLAB/Octave" takes the reader conceptually through from the fundamental mechanics of lift to the stage of actually being able to make practical calculations and predictions of the coefficient of lift for realistic wing profile and planform geometries. The classical framework and methods of aerodynamics are covered in detail and the reader is shown how they may be used to develop simple yet powerful MATLAB or Octave programs that accurately predict and visualise the dynamics of real wing shapes, using lumped vortex, panel, and vortex lattice methods. This book contains all the mathematical development and formulae required in standard incompressible aerodynamics as well as dozens of small but complete working programs which can be put to use immediately using either the popular MATLAB or free Octave computional modelling packages. Key features: Synthesizes the classical foundations of aerodynamics with hands-on computation, emphasizing interactivity and visualization.Includes complete source code for all programs, all listings having been tested for compatibility with both MATLAB and Octave.Companion website (www.wiley.com/go/mcbain) hosting codes and solutions. "Theory of Lift: Introductory Computational Aerodynamics in MATLAB/Octave" is an introductory text for graduate and senior undergraduate students on aeronautical and aerospace engineering courses and also forms a valuable reference for engineers and designers.
Highlighting the latest advances in nonparametric and semiparametric statistics, this book gathers selected peer-reviewed contributions presented at the 4th Conference of the International Society for Nonparametric Statistics (ISNPS), held in Salerno, Italy, on June 11-15, 2018. It covers theory, methodology, applications and computational aspects, addressing topics such as nonparametric curve estimation, regression smoothing, models for time series and more generally dependent data, varying coefficient models, symmetry testing, robust estimation, and rank-based methods for factorial design. It also discusses nonparametric and permutation solutions for several different types of data, including ordinal data, spatial data, survival data and the joint modeling of both longitudinal and time-to-event data, permutation and resampling techniques, and practical applications of nonparametric statistics. The International Society for Nonparametric Statistics is a unique global organization, and its international conferences are intended to foster the exchange of ideas and the latest advances and trends among researchers from around the world and to develop and disseminate nonparametric statistics knowledge. The ISNPS 2018 conference in Salerno was organized with the support of the American Statistical Association, the Institute of Mathematical Statistics, the Bernoulli Society for Mathematical Statistics and Probability, the Journal of Nonparametric Statistics and the University of Salerno.
- includes MATLABr fundamentals, matrices, arrays, general graphics and specialized plots in quality assurance problems, script files, ordinary and partial differential equations - gives calculation of six sigma, total quality management, time series forecasting, reliability, process improvement, metrology, quality control and assurance, measurement and testing techniques - provides tools for graphical presentation, basic and special statistics and testing, ordinary and partial differential solvers, and fitting tools - includes comprehensive command information in tables Many books are available on MATLABr programming for engineers in general or in some specific area, but none in the highly topical field of quality assurance (QA). MATLABr in quality assurance sciences fills this gap as a compact guide for students, engineers, and scientists in this field. It concentrates on MATLABr fundamentals with examples of application to a wide range of current problems from general, nano and bio-technology, and statistical control, to medicine and industrial management. Examples cover both the school and advanced level; comprising calculations of total quality management, six sigma, time series, process improvement, metrology, quality control, human factors in quality assurance, measurement and testing techniques, quality project and function management, and customer satisfaction. The book covers key topics, including: the basics of software with examples; graphics and representations; numerical computation, scripts and functions for QA calculations; ODE and PDEPE solvers applied to QA problems; curve fitting and time series tool interfaces in calculations of quality; and statistics calculations applied to quality testing.
30th European Symposium on Computer Aided Chemical Engineering, Volume 47 contains the papers presented at the 30th European Symposium of Computer Aided Process Engineering (ESCAPE) event held in Milan, Italy, May 24-27, 2020. It is a valuable resource for chemical engineers, chemical process engineers, researchers in industry and academia, students, and consultants for chemical industries.
Multi-Paradigm Modelling for Cyber-Physical Systems explores modeling and analysis as crucial activities in the development of Cyber-Physical Systems, which are inherently cross-disciplinary in nature and require distinct modeling techniques related to different disciplines, as well as a common background knowledge. This book will serve as a reference for anyone starting in the field of CPS who needs a solid foundation of modeling, including a comprehensive introduction to existing techniques and a clear explanation of their advantages and limitations. This book is aimed at both researchers and practitioners who are interested in various modeling paradigms across computer science and engineering.
Dive into the new SAP C/4HANA suite. Understand how SAP C/4HANA handles marketing, commerce, sales, service, and customer data processes-and identify which solutions fit your organization's CX needs. Then explore integrations to SAP S/4HANA, extensions using SAP Cloud Platform, and applied artificial intelligence using SAP Leonardo. Learn how can serve your customers better-from the demand chain all the way down to the supply chain! Key Features: Get to know SAP C/4HANA, the new SAP Customer Experience suite. Explore marketing, commerce, sales, service, and customers.
"If mathematical modeling is the process of turning real phenomena into mathematical abstractions, then numerical computation is largely about the transformation from abstract mathematics to concrete reality. Many science and engineering disciplines have long benefited from the tremendous value of the correspondence between quantitative information and mathematical manipulation." -from the Preface Fundamentals of Numerical Computation is an advanced undergraduate-level introduction to the mathematics and use of algorithms for the fundamental problems of numerical computation: linear algebra, finding roots, approximating data and functions, and solving differential equations. The book is organized with simpler methods in the first half and more advanced methods in the second half, allowing use for either a single course or a sequence of two courses. The authors take readers from basic to advanced methods, illustrating them with over 200 self-contained MATLAB functions and examples designed for those with no prior MATLAB experience. Although the text provides many examples, exercises, and illustrations, the aim of the authors is not to provide a cookbook per se, but rather an exploration of the principles of cooking. Professors Driscoll and Braun have developed an online resource that includes well-tested materials related to every chapter. Among these materials are lecture-related slides and videos, ideas for student projects, laboratory exercises, computational examples and scripts, and all the functions presented in the book.
R is a powerful and free software system for data analysis and graphics, with over 5,000 add-on packages available. This book introduces R using SAS and SPSS terms with which you are already familiar. It demonstrates which of the add-on packages are most like SAS and SPSS and compares them to R's built-in functions. It steps through over 30 programs written in all three packages, comparing and contrasting the packages' differing approaches. The programs and practice datasets are available for download. The glossary defines over 50 R terms using SAS/SPSS jargon and again using R jargon. The table of contents and the index allow you to find equivalent R functions by looking up both SAS statements and SPSS commands. When finished, you will be able to import data, manage and transform it, create publication quality graphics, and perform basic statistical analyses. This new edition has updated programming, an expanded index, and even more statistical methods covered in over 25 new sections.
Recommended by Bill Gates A thought-provoking and wide-ranging exploration of machine learning and the race to build computer intelligences as flexible as our own In the world's top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask. In The Master Algorithm, Pedro Domingos lifts the veil to give us a peek inside the learning machines that power Google, Amazon, and your smartphone. He assembles a blueprint for the future universal learner--the Master Algorithm--and discusses what it will mean for business, science, and society. If data-ism is today's philosophy, this book is its bible.
Cohesively Incorporates Statistical Theory with R Implementation Since the publication of the popular first edition of this comprehensive textbook, the contributed R packages on CRAN have increased from around 1,000 to over 6,000. Designed for an intermediate undergraduate course, Probability and Statistics with R, Second Edition explores how some of these new packages make analysis easier and more intuitive as well as create more visually pleasing graphs. New to the Second Edition Improvements to existing examples, problems, concepts, data, and functions New examples and exercises that use the most modern functions Coverage probability of a confidence interval and model validation Highlighted R code for calculations and graph creation Gets Students Up to Date on Practical Statistical Topics Keeping pace with today's statistical landscape, this textbook expands your students' knowledge of the practice of statistics. It effectively links statistical concepts with R procedures, empowering students to solve a vast array of real statistical problems with R. Web Resources A supplementary website offers solutions to odd exercises and templates for homework assignments while the data sets and R functions are available on CRAN.
The Feature-Driven Method for Structural Optimization details a novel structural optimization method within a CAD framework, integrating structural optimization and feature-based design. The book presents cutting-edge research on advanced structures and introduces the feature-driven structural optimization method by regarding engineering features as basic design primitives. Consequently, it presents a method that allows structural optimization and feature design to be done simultaneously so that feature attributes are preserved throughout the design process. The book illustrates and supports the effectiveness of the method described, showing potential applications through numerical modeling techniques and programming. This volume presents a high-performance optimization method adapted to engineering structures-a novel perspective that will help engineers in the computation, modeling and design of advanced structures.
Nonlinear Parameter Optimization Using RJohn C. Nash, Telfer School of Management, University of Ottawa, Canada A systematic and comprehensive treatment of optimization software using RIn recent decades, optimization techniques have been streamlined by computational and artificial intelligence methods to analyze more variables, especially under non-linear, multivariable conditions, more quickly than ever before.Optimization is an important tool for decision science and for the analysis of physical systems used in engineering. Nonlinear Parameter Optimization with R explores the principal tools available in R for function minimization, optimization, and nonlinear parameter determination and features numerous examples throughout. Nonlinear Parameter Optimization with R: - Provides a comprehensive treatment of optimization techniques- Examines optimization problems that arise in statistics and how to solve them using R- Enables researchers and practitioners to solve parameter determination problems- Presents traditional methods as well as recent developments in R- Is supported by an accompanying website featuring R code, examples and datasets Researchers and practitioners who have to solve parameter determination problems who are users of R but are novices in the field optimization or function minimization will benefit from this book. It will also be useful for scientists building and estimating nonlinear models in various fields such as hydrology, sports forecasting, ecology, chemical engineering, pharmaco-kinetics, agriculture, economics and statistics.
This open access book provides insights into the novel Locally Refined B-spline (LR B-spline) surface format, which is suited for representing terrain and seabed data in a compact way. It provides an alternative to the well know raster and triangulated surface representations. An LR B-spline surface has an overall smooth behavior and allows the modeling of local details with only a limited growth in data volume. In regions where many data points belong to the same smooth area, LR B-splines allow a very lean representation of the shape by locally adapting the resolution of the spline space to the size and local shape variations of the region. The iterative method can be modified to improve the accuracy in particular domains of a point cloud. The use of statistical information criterion can help determining the optimal threshold, the number of iterations to perform as well as some parameters of the underlying mathematical functions (degree of the splines, parameter representation). The resulting surfaces are well suited for analysis and computing secondary information such as contour curves and minimum and maximum points. Also deformation analysis are potential applications of fitting point clouds with LR B-splines.
Quicken is one of the many convenient ways to keep track of personal finances, but many people are unaware of Quicken's power and end up using only the basic features. And sometimes Quicken seems to raise more questions than it answers: Return of capital from stock? "Net worth"? What are they and why do you need to know about them? Luckily, "Quicken 2008: The Missing Manual" picks up where Quicken's help resources leave off. You'll find step-by-step instructions for using the most useful Quicken features, including those you may not have quite understood, let alone mastered, such as budgeting, recording investment transactions, archiving Quicken data files, and so on. You also learn why and when to use specific features, and which ones would be most useful in your situation." Quicken 2008: The Missing Manual" helps you: set up Quicken to take care of your specific needs; follow your money from the moment you earn it; make deposits, pay for expenses, track the things you own and how much you owe; take care of financial tasks online, and quickly reconcile your accounts; create and use budgets and track your investments; generate reports to prepare your tax returns and evaluate your financial fitness; and a lot more. This book is designed to accommodate readers at every technical level. If you're a first-time Quicken user, special boxes with the title "Up To Speed" provide the introductory information you need to understand the topic at hand. For advanced users, there are similar boxes called "Power Users' Clinic" that offer more technical tips, tricks, and shortcuts for the experienced Quicken fan. For a topic as important as your personal finances, why trust anything else?
R, an Open Source software, has become the "de facto" statistical computing environment. It has an excellent collection of data manipulation and graphics capabilities. It is extensible and comes with a large number of packages that allow statistical analysis at all levels - from simple to advanced - and in numerous fields including Medicine, Genetics, Biology, Environmental Sciences, Geology, Social Sciences and much more. The software is maintained and developed by academicians and professionals and as such, is continuously evolving and up to date. "Statistics and Data with R" presents an accessible guide to data manipulations, statistical analysis and graphics using R. Assuming no previous knowledge of statistics or R, the book includes: A comprehensive introduction to the R language. An integrated approach to importing and preparing data for analysis, exploring and analyzing the data, and presenting results. Over 300 examples, including detailed explanations of the R scripts used throughout. Over 100 moderately large data sets from disciplines ranging from Biology, Ecology and Environmental Science to Medicine, Law, Military and Social Sciences. A parallel discussion of analyses with the normal density, proportions (binomial), counts (Poisson) and bootstrap methods. Two extensive indexes that include references to every R function (and its arguments and packages used in the book and to every introduced concept. An accompanying Wiki website, http: //turtle.gis.umn.eduincludes all the scripts and data used in the book. The website also features a solutions manual, providing answers to all of the excercises presented in the book. Visitors are invited to download/upload data andscripts and share comments, suggestions and questions with other visitors. Students, researchers and practitioners will find this to be both a valuable learning resource in statistics and R and an excellent reference book.
This book will help readers understand fundamental and advanced statistical models and deep learning models for robust speaker recognition and domain adaptation. This useful toolkit enables readers to apply machine learning techniques to address practical issues, such as robustness under adverse acoustic environments and domain mismatch, when deploying speaker recognition systems. Presenting state-of-the-art machine learning techniques for speaker recognition and featuring a range of probabilistic models, learning algorithms, case studies, and new trends and directions for speaker recognition based on modern machine learning and deep learning, this is the perfect resource for graduates, researchers, practitioners and engineers in electrical engineering, computer science and applied mathematics.
This book presents the latest numerical solutions to initial value problems and boundary value problems described by ODEs and PDEs. The author offers practical methods that can be adapted to solve wide ranges of problems and illustrates them in the increasingly popular open source computer language R, allowing integration with more statistically based methods. The book begins with standard techniques, followed by an overview of 'high resolution' flux limiters and WENO to solve problems with solutions exhibiting high gradient phenomena. Meshless methods using radial basis functions are then discussed in the context of scattered data interpolation and the solution of PDEs on irregular grids. Three detailed case studies demonstrate how numerical methods can be used to tackle very different complex problems. With its focus on practical solutions to real-world problems, this book will be useful to students and practitioners in all areas of science and engineering, especially those using R.
Dispel myths and reap the benefits of this robust accounting software! If you're like most business people, accounting is the last thing you want to spend lots of time doing. This friendly, no-nonsense guide gets you up to speed, highlighting the most useful and practical features, disproving common misconceptions, and letting you in on the best tips and tricks -- all in plain English! The plain truth -- see how to set up Dynamics GP, get around the program, create a company, and build an effective chart of accounts Module madness -- get the details on the modules you'll use most often in the Purchasing, Sales, Inventory, and Financial series Collect -- bill customers, manage receipts, and easily match payments to invoices Bank reconciliation -- track processed payments and deposits against your bank statements Year-end stuff -- close your books and print reports from all the data you've collected Keep data up to date -- use Professional Services Tools and utilities to find and fix data discrepancies Lock it down -- discover how to protect your database and set up a disaster recovery plan It's in the Office -- leverage the interoperability between Dynamics GP and Microsoft Office applications Customize -- make GP fit your business perfectly Open the book and find: How to make SmartList work for you Set-up tips to make GP's home page more efficient All about the Customer Card Ways to set up vendors quickly and easily How to save keystrokes with Quick Journal and batch frequency Shortcuts for easy report printing Secrets of a hassle-free upgrade What your disaster recovery plan should contain
For over two decades, this comprehensive manual has been the standard introduction and complete reference for writing articles and books containing mathematical formulas. If the reader requires a streamlined approach to learning LaTeX for composing everyday documents, Gratzer's (c) 2014 Practical LaTeX may also be a good choice. In this carefully revised fifth edition, the Short Course has been brought up to date and reflects a modern and practical approach to LaTeX usage. New chapters have been added on illustrations and how to use LaTeX on an iPad. Key features: An example-based, visual approach and a gentle introduction with the Short Course A detailed exposition of multiline math formulas with a Visual Guide A unified approach to TeX, LaTeX, and the AMS enhancements A quick introduction to creating presentations with formulas From earlier reviews: Gratzer's book is a solution. -European Mathematical Society Newsletter There are several LaTeX guides, but this one wins hands down for the elegance of its approach and breadth of coverage. -Amazon.com, Best of 2000, Editor's choice A novice reader will be able to learn the most essential features of LaTeX sufficient to begin typesetting papers within a few hours of time... An experienced TeX user, on the other hand, will find a systematic and detailed discussion of LaTeX fea tures. -Report on Mathematical Physics A very helpful and useful tool for all scientists and engineers. -Review of Astronomical Tools
Get the most out of your Materials Management implementation with this updated, comprehensive guide to configuration and functionality. You'll learn the ins and outs of Materials Management in SAP, from goods receipt and invoice verification to early warning systems and special procurement types. Dive into master data and other configuration tasks to ensure your MM system is optimized for your logistics needs! Materials Management Functionality: Learn to use MM for essential tasks like requesting quotations, purchase orders, and inventory management and for more advanced tasks like forecasting, using classification systems, and handling special procurement types. Business Scenarios and Examples: Configure settings for critical processes, and explore master data for materials and vendors. Cloud Migration and SAP S/4HANA: Expand your understanding of MM processes with expert advice, real-world examples, and sample business scenarios. Highlights: Materials master data Vendor master data Purchasing information data Batch management External Services Management Material requirements planning (MRP) Inventory management Goods issue/goods receipt (GI/GR) Material Ledger Balance sheet valuation Invoice verification Document management |
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