International Association for Statistical Computing The International Association for Statistical Computing (IASC) is a Section of the International Statistical Institute. The objectives of the Association are to foster world-wide interest in e?ective statistical computing and to - change technical knowledge through international contacts and meetings - tween statisticians, computing professionals, organizations, institutions, g- ernments and the general public. The IASC organises its own Conferences, IASC World Conferences, and COMPSTAT in Europe. The 17th Conference of ERS-IASC, the biennial meeting of European - gional Section of the IASC was held in Rome August 28 - September 1, 2006. This conference took place in Rome exactly 20 years after the 7th COMP- STAT symposium which was held in Rome, in 1986. Previous COMPSTAT conferences were held in: Vienna (Austria, 1974); West-Berlin (Germany, 1976); Leiden (The Netherlands, 1978); Edimbourgh (UK, 1980); Toulouse (France, 1982); Prague (Czechoslovakia, 1984); Rome (Italy, 1986); Copenhagen (Denmark, 1988); Dubrovnik (Yugoslavia, 1990); Neuch atel (Switzerland, 1992); Vienna (Austria,1994); Barcelona (Spain, 1996);Bristol(UK,1998);Utrecht(TheNetherlands,2000);Berlin(Germany, 2002); Prague (Czech Republic, 2004).

Many successful project managers are beginning to utilize Microsoft SharePoint to drive their projects and operational initiatives. SharePoint Server provides teams with a centralized location for project information and facilitates collaboration between project team members. The intention of this book is to provide a hands-on case study that you can follow to create a complete project management information system (PMIS) using SharePoint Server 2010.
What you'll learn Create custom lists and content types Handle incoming emails Use web parts to customize your SharePoint portal Implement key performance indicators (KPIs) Integrate Excel charting capability Build a state machine workflow Create custom forms using InfoPath Develop a simple approach for prioritizing requirements Provide tools for managing agile development (sprints, backlog, burn down, etc.) Communicate development and testing metrics Who this book is for

This book is intended primarily for project managers and IT professionals that would like to leverage Microsoft's SharePoint technologies to help manage projects within their organization. Also, developers who are responsible for implementing a PMIS will find this book invaluable. Most of the projects presented in this book can be implemented without writing any code. Table of Contents Introduction Collecting Requirements Processing Incoming E-mail Managing Requirements Supporting Discussions User Stories Project Backlog Iteration Backlog Burndown Charts Getting Organized Creating Test Cases Reporting Defects Testing Metrics Workflow Tasks State Machine Workflows Creating Custom Forms

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. This book is a nuts-and-bolts guide to working with the TI-Nspire, providing everything you need to get up and running and helping you get the most out of this high-powered math tool.Texas Instruments' TI-Nspire graphing calculator is perfect for high school and college students in advanced algebra and calculus classes as well as students taking the SAT, PSAT, and ACT examsThis fully updated guide covers all enhancements to the TI-Nspire, including the touchpad and the updated software that can be purchased along with the deviceShows how to get maximum value from this versatile math tool

With updated screenshots and examples, "TI-Nspire For Dummies" provides practical, hands-on instruction to help students make the most of this revolutionary graphing calculator.

An elementary first course for students in mathematics and engineering

Practical in approach: examples of code are provided for students to debug, and tasks - with full solutions - are provided at the end of each chapter

Includes a glossary of useful terms, with each term supported by an example of the syntaxes commonly encountered

This new edition of the successful multi-disciplinary text Statistical Modelling in GLIM takes into account new developments in both statistical software and statistical modelling. Including three new chapters on mixture and random effects models, it provides a comprehensive treatment of the theory of statistical modelling with generalised linear models with an emphasis on applications to practical problems and an expanded discussion of statistical theory. A wide range of case studies is also provided, using the normal, binomial, Poisson, multinomial, gamma, exponential and Weibull distributions. This book is ideal for graduates and research students in applied statistics and a wide range of quantitative disciplines, including biology, medicine and the social sciences. Professional statisticians at all levels will also find it an invaluable desktop companion.

The second edition of this popular guide demonstrates the process of entering and analyzing data using the latest version of SPSS (12.0), and is also appropriate for those using earlier versions of SPSS. The book is easy to follow because all procedures are outlined in a step-by-step format designed for the novice user. Students are introduced to the rationale of statistical tests and detailed explanations of results are given through clearly annotated examples of SPSS output. Topics covered range from descriptive statistics through multiple regression analysis. In addition, this guide includes topics not typically covered in other books such as probability theory, interaction effects in analysis of variance, factor analysis, and scale reliability. Chapter exercises reinforce the text examples and may be performed for further practice, for homework assignments, or in computer laboratory sessions.

This book can be used in two ways: as a stand-alone manual for students wishing to learn data analysis techniques using SPSS for Windows, or in research and statistics courses to be used with a basic statistics text. The book provides hands-on experience with actual data sets, helps students choose appropriate statistical tests, illustrates the meaning of results, and provides exercises to be completed for further practice or as homework assignments.

Susan B. Gerber, Ph.D. is Research Assistant Professor of Education at State University of New York at Buffalo. She is director of the Educational Technology program and holds degrees in Statistics and Educational Psychology.

Kristin Voelkl Finn, Ph.D. is Assistant Professor of Education at Canisius College. She teaches graduate courses in research methodology and conducts research on adolescent problem behavior.

Over two hundred novel and innovative computer algebra worksheets or "recipes" will enable readers in engineering, physics, and mathematics to easily and rapidly solve and explore most problems they encounter in their mathematical physics studies. While the aim of this text is to illustrate applications, a brief synopsis of the fundamentals for each topic is presented, the topics being organized to correlate with those found in traditional mathematical physics texts. The recipes are presented in the form of stories and anecdotes, a pedagogical approach that makes a mathematically challenging subject easier and more fun to learn.
Key features:

* Uses the MAPLE computer algebra system to allow the reader to easily and quickly change the mathematical models and the parameters and then generate new answers

* No prior knowledge of MAPLE is assumed; the relevant MAPLE commands are introduced on a need-to-know basis

* All recipes are contained on a CD-ROM provided with the text

* All MAPLE commands are indexed for easy reference

* A classroom-tested story/anecdote format is used, accompanied with amusing or thought-provoking quotations

* Study problems, which are presented as Supplementary Recipes, are fully solved and annotated and also provided on the CD-ROM

This is a self-contained and standalone text, similar in style and format to Computer Algebra Recipes: A Gourmet's Guide to Mathematical Models of Science (ISBN 0-387-95148-2), Springer New York 2001 and Computer Algebra Recipes for Classical Mechanics (ISBN 0-8176-4291-9), BirkhAuser 2003. Computer Algebra Recipes for Mathematical Physics may be used in the classroom, for self-study, as a reference, or asa text for an online course.

Technology/Engineering/Mechanical

Provides all the tools needed to begin solving optimization problems using MATLAB(R)

The Second Edition of Applied Optimization with MATLAB(R) Programming enables readers to harness all the features of MATLAB(R) to solve optimization problems using a variety of linear and nonlinear design optimization techniques. By breaking down complex mathematical concepts into simple ideas and offering plenty of easy-to-follow examples, this text is an ideal introduction to the field. Examples come from all engineering disciplines as well as science, economics, operations research, and mathematics, helping readers understand how to apply optimization techniques to solve actual problems.

This Second Edition has been thoroughly revised, incorporating current optimization techniques as well as the improved MATLAB(R) tools. Two important new features of the text are:

Introduction to the scan and zoom method, providing a simple, effective technique that works for unconstrained, constrained, and global optimization problems

New chapter, Hybrid Mathematics: An Application, using examples to illustrate how optimization can develop analytical or explicit solutions to differential systems and data-fitting problems

Each chapter ends with a set of problems that give readers an opportunity to put their new skills into practice. Almost all of the numerical techniques covered in the text are supported by MATLAB(R) code, which readers can download on the text's companion Web site www.wiley.com/go/venkat2e and use to begin solving problems on their own.

This text is recommended for upper-level undergraduate and graduate students in all areas of engineering as well as other disciplines that use optimization techniques to solve design problems.

Die effektive und effiziente Gestaltung von Dienstleistungen wird fur Unternehmen immer entscheidender. Dies gilt nicht nur in den bewahrten Dienstleistungsbranchen, sondern auch verstarkt fur industrielle Anwendungen, bei denen der Dienstleistungsanteil am klassischen materiellen Produkt permanent steigt. Die damit verbundene zunehmende Verflechtung von Unternehmen sowie die gestiegene Produkt- und Prozesskomplexitat erfordern eine interdisziplinare Herangehensweise zwischen Dienstleistungsmanagement, Produktion und Informationstechnologie. Dieser Band stellt aktuelle und innovative Konzepte fur die modellbasierte Entwicklung, Erbringung und kontinuierliche Verbesserung von Dienstleistungen sowie ihre Einbettung in hybride Leistungsangebote vor. Neben dem Stand der Forschung zeigen zahlreiche Branchenszenarien das Potenzial und die praktische Umsetzbarkeit der Dienstleistungsmodellierung auf. Das Buch richtet sich an Dozenten und Studenten der Betriebswirtschaftslehre, der Ingenieurwissenschaften und der Wirtschaftsinformatik sowie an Praktiker in Unternehmen, die sich mit der modellbasierten Gestaltung von Dienstleistungen befassen.

This volume brings together the main results in the field of Bayesian Optimization (BO), focusing on the last ten years and showing how, on the basic framework, new methods have been specialized to solve emerging problems from machine learning, artificial intelligence, and system optimization. It also analyzes the software resources available for BO and a few selected application areas. Some areas for which new results are shown include constrained optimization, safe optimization, and applied mathematics, specifically BO's use in solving difficult nonlinear mixed integer problems. The book will help bring readers to a full understanding of the basic Bayesian Optimization framework and gain an appreciation of its potential for emerging application areas. It will be of particular interest to the data science, computer science, optimization, and engineering communities.

This book is dedicated to the systematization and development of models, methods, and algorithms for queuing systems with correlated arrivals. After first setting up the basic tools needed for the study of queuing theory, the authors concentrate on complicated systems: multi-server systems with phase type distribution of service time or single-server queues with arbitrary distribution of service time or semi-Markovian service. They pay special attention to practically important retrial queues, tandem queues, and queues with unreliable servers. Mathematical models of networks and queuing systems are widely used for the study and optimization of various technical, physical, economic, industrial, and administrative systems, and this book will be valuable for researchers, graduate students, and practitioners in these domains.

This book is published open access under a CC BY 4.0 license. This book presents computer programming as a key method for solving mathematical problems. This second edition of the well-received book has been extensively revised: All code is now written in Python version 3.6 (no longer version 2.7). In addition, the two first chapters of the previous edition have been extended and split up into five new chapters, thus expanding the introduction to programming from 50 to 150 pages. Throughout the book, the explanations provided are now more detailed, previous examples have been modified, and new sections, examples and exercises have been added. Also, a number of small errors have been corrected. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style employed is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows students to write simple programs for solving common mathematical problems with numerical methods in the context of engineering and science courses. The emphasis is on generic algorithms, clean program design, the use of functions, and automatic tests for verification.

Experience learning made easy - and quickly teach yourself how to manage the complete project life cycle with Project 2013. With Step by Step, you set the pace - building and practicing the skills you need, just when you need them

Work with Project 2013 on your PC or touch-enabled deviceBuild and fine-tune your project planSchedule tasks and milestones, and assign resourcesTrack progress and costs, and manage variancesTroubleshoot delays and budget overrunsCustomize Gantt chart views, tables, and calendarsLearn project-management best practices

Gain the R programming language fundamentals for doing the applied statistics useful for data exploration and analysis in data science and data mining. This book covers topics ranging from R syntax basics, descriptive statistics, and data visualizations to inferential statistics and regressions. After learning R's syntax, you will work through data visualizations such as histograms and boxplot charting, descriptive statistics, and inferential statistics such as t-test, chi-square test, ANOVA, non-parametric test, and linear regressions. Learn R for Applied Statistics is a timely skills-migration book that equips you with the R programming fundamentals and introduces you to applied statistics for data explorations. What You Will Learn Discover R, statistics, data science, data mining, and big data Master the fundamentals of R programming, including variables and arithmetic, vectors, lists, data frames, conditional statements, loops, and functions Work with descriptive statistics Create data visualizations, including bar charts, line charts, scatter plots, boxplots, histograms, and scatterplots Use inferential statistics including t-tests, chi-square tests, ANOVA, non-parametric tests, linear regressions, and multiple linear regressions Who This Book Is For Those who are interested in data science, in particular data exploration using applied statistics, and the use of R programming for data visualizations.

"JMP Start Statistics: A Guide to Statistics and Data Analysis Using JMP, Fifth Edition," is the perfect mix of software manual and statistics text. Authors John Sall, Ann Lehman, Mia Stephens, and Lee Creighton provide hands-on tutorials with just the right amount of conceptual and motivational material to illustrate how to use the intuitive interface for data analysis in JMP. Each chapter features concept-specific tutorials, examples, brief reviews of concepts, step-by-step illustrations, and exercises.

"JMP Start Statistics, Fifth Edition," includes many new features of JMP 10, including an enhanced ability to manage a JMP session by easily tracking open and recently opened JMP tables; scripts, analyses, JMP projects, and other files; vastly expanded tools for instructors to demonstrate statistical concepts and interactive scripts to help students grasp difficult topics; Split-Plot designs with examples; examples of Graph Builder and Control Chart Builder; and new features that make the software easier to use.

Using a visual data analysis approach, wavelet concepts are explained in a way that is intuitive and easy to understand. Furthermore, in addition to wavelets, a whole range of related signal processing techniques such as wavelet packets, local cosine analysis, and matching pursuits are covered, and applications of wavelet analysis are illustrated -including nonparametric function estimation, digital image compression, and time-frequency signal analysis. This book and software package is intended for a broad range of data analysts, scientists, and engineers. While most textbooks on the subject presuppose advanced training in mathematics, this book merely requires that readers be familiar with calculus and linear algebra at the undergraduate level.

The book is aimed at Project Management Professionals who are casual or new users and understand the software basics but require a short and snappy guide. It is the sort of book that may be read without a computer on the bus, train or plane. This book quickly gets down to the issues that many people grapple with when trying to use some of the more advanced features of the software and enlightens readers on the traps that some users fall into and how to avoid them. It demonstrates how the software ticks and explains some tricks that may be used to become more productive with the software and generate better schedules. Suitable for people who understand the basics of Microsoft Project but want a short guide to give them insight into the less intuitive features of the software. It is packed with screen shots, constructive tips and is written in plain English. The book is based on the Microsoft Project 365 and 2021 but may be used with earlier versions of Microsoft Project as this book points out the differences where appropriate. The book picks out many of the key aspects from the author's exiting books and adds a substantial amount of new and original text to produce a pocket guide that omits describing the intuitive and obvious functions and concentrates on the issues that many users get stuck on or find hard to understand.

Go from total MATLAB newbie to plotting graphs and solving equations in a flash! MATLAB is one of the most powerful and commonly used tools in the STEM field. But did you know it doesn't take an advanced degree or a ton of computer experience to learn it? MATLAB For Dummies is the roadmap you've been looking for to simplify and explain this feature-filled tool. This handy reference walks you through every step of the way as you learn the MATLAB language and environment inside-and-out. Starting with straightforward basics before moving on to more advanced material like Live Functions and Live Scripts, this easy-to-read guide shows you how to make your way around MATLAB with screenshots and newly updated procedures. It includes: A comprehensive introduction to installing MATLAB, using its interface, and creating and saving your first file Fully updated to include the 2020 and 2021 updates to MATLAB, with all-new screenshots and up-to-date procedures Enhanced debugging procedures and use of the Symbolic Math Toolbox Brand new instruction on working with Live Scripts and Live Functions, designing classes, creating apps, and building projects Intuitive walkthroughs for MATLAB's advanced features, including importing and exporting data and publishing your work Perfect for STEM students and new professionals ready to master one of the most powerful tools in the fields of engineering, mathematics, and computing, MATLAB For Dummies is the simplest way to go from complete newbie to power user faster than you would have thought possible.

Der Begriff "Open-Source-Software" wurde vor knapp zehn Jahren gepragt und hat inzwischen eine feste Position im IT-Markt erobert. Heute wird Open-Source-Software von praktisch allen im IT-Markt vertretenen Unternehmen entwickelt. In dem vorliegenden Buch werden folgende Fragen erortert: Wie wirkt sich die zunehmende Verbreitung und Nutzung von Open-Source-Software und offenen Standards auf Wettbewerb aus? Konnen wirtschaftspolitische Massnahmen die Vorteile eines offenen Wettbewerbs und die Nutzung neuer Innovationspotenziale unterstutzen? Es wird ein Beitrag geleistet zum okonomischen Verstandnis der Konzepte von Open-Source-Software und offenen Standards. Theoretische Analyse und wirtschaftspolitische Praxis werden miteinander verbunden. Anhand eines internationalen Vergleichs werden verschiedene nationale Open-Source-Strategien analysiert, bewertet und weiterer Handlungsbedarf angezeigt mit Vorschlagen, wie Wettbewerb auf Softwaremarkten offener gestaltet werden kann."

Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Need to Learn MATLAB? Problem SOLVED! Get started using MATLAB right away with help from this hands-on guide. MATLAB Demystified offers an effective and enlightening method for learning how to get the most out this powerful computational mathematics tool. Using an easy-to-follow format, this book explains the basics of MATLAB up front. You'll find out how to plot functions, solve algebraic equations, and compute integrals. You'll also learn how to solve differential equations, generate numerical solutions of ODEs, and work with special functions. Packed with hundreds of sample equations and explained solutions, and featuring end-of-chapter quizzes and a final exam, this book will teach you MATLAB essentials in no time at all. This self-teaching guide offers: The quickest way to get up and running on MATLAB Hundreds of worked examples with solutions Coverage of MATLAB 7 A quiz at the end of each chapter to reinforce learning and pinpoint weaknesses A final exam at the end of the book A time-saving approach to performing better on homework or on the job Simple enough for a beginner, but challenging enough for an advanced user, MATLAB Demystified is your shortcut to computational precision.

ABAP to the Future is back, and better than ever! Looking for the latest in ABAP syntax? The code examples are fully rewritten. Need to start working in the cloud with the ABAP RESTful application programming model? We've got you covered. Got a new IDE like SAP Business Application Studio? We'll show you the ins and outs of your environment. From abapGit and ABAP2XLSX to SAPUI5 and Web Dynpro ABAP, this new edition has everything you need to be on the cutting edge!

Take your supply chain to the cloud! Walk through the SAP Integrated Business Planning applications-S&OP, demand, response and supply, demand-driven MRP, and inventory. Then learn to monitor and control these processes. See how to set up and use your SAP IBP system, from planning areas to key figures. With coverage of intelligent visibility, SAP IBP for demand-driven replenishment, and more, you can be sure you're getting the latest information on supply chain planning with SAP! Highlights include: 1) Planning model 2) Planning areas 3) Sales and operations planning (S&OP) 4) Demand planning and forecasting 5) Supply planning 6) Response planning 7) Inventory planning 8) Demand-driven replenishment 9) SAP Supply Chain Control Tower 10) Implementation methodology 11) Case studies

The rules and practices for Scrum--a simple process for managing complex projects--are few, straightforward, and easy to learn. But Scrum's simplicity itself--its lack of prescription--can be disarming, and new practitioners often find themselves reverting to old project management habits and tools and yielding lesser results. In this illuminating series of case studies, Scrum co-creator and evangelist Ken Schwaber identifies the real-world lessons--the successes and failures--culled from his years of experience coaching companies in agile project management. Through them, you'll understand how to use Scrum to solve complex problems and drive better results--delivering more valuable software faster. Gain the foundation in Scrum theory--and practice--you need to: Rein in even the most complex, unwieldy projects Effectively manage unknown or changing product requirements Simplify the chain of command with self-managing development teams Receive clearer specifications--and feedback--from customers Greatly reduce project planning time and required tools Build--and release--products in 30-day cycles so clients get deliverables earlier Avoid missteps by regularly inspecting, reporting on, and fine-tuning projects Support multiple teams working on a large-scale project from many geographic locations Maximize return on investment

This book discusses questions of numerical solutions of applied problems on parallel computing systems. Nowadays, engineering and scientific computations are carried out on parallel computing systems, which provide parallel data processing on a few computing nodes. In the development of up-to-date applied software, this feature of computers must be taken into account for the maximum efficient usage of their resources. In constructing computational algorithms, we should separate relatively independent subproblems in order to solve them on a single computing node.

This textbook teaches crucial statistical methods to answer research questions using a unique range of statistical software programs, including MINITAB and R. This textbook is developed for undergraduate students in agriculture, nursing, biology and biomedical research. Graduate students will also find it to be a useful way to refresh their statistics skills and to reference software options. The unique combination of examplesis approached using MINITAB and R for their individual strengths. Subjects covered include among others data description, probability distributions, experimental design, regression analysis, randomized design and biological assay. Unlike other biostatistics textbooks, this text also includes outliers, influential observations in regression and an introduction to survival analysis. Material is taken from the author's extensive teaching and research in Africa, USA and the UK. Sample problems, references and electronic supplementary material accompany each chapter."