E(lectronic)- und M(obile)-Learning: das Lernen und Lehren mittels Informations- und Kommunikationstechnologien wird bereits in vielen Bereichen erfolgreich eingesetzt. In (Hoch)schulen sowie in der beruflichen Aus-, Fort- und Weiterbildung von Auszubildenden bis hin zu Top-Managern. Dieser Sammelband beschreibt den Status Quo und aktuelle Projekte. Er identifiziert und analysiert wichtige E-Learning-Trends und zukunftsgerichtete Entwicklungen.

This book shows the capabilities of Microsoft Excel in teaching marketing statistics effectively. It is a step-by-step, exercise-driven guide for students and practitioners who need to master Excel to solve practical marketing problems. If understanding statistics isn't your strongest suit, you are not especially mathematically inclined, or if you are wary of computers, this is the right book for you.Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in marketing courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. Excel 2019 for Marketing Statistics: A Guide to Solving Practical Problems capitalizes on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work. In this new edition, each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand marketing problems. Practice problems are provided at the end of each chapter with their solutions in an appendix. Separately, there is a full practice test (with answers in an appendix) that allows readers to test what they have learned.

Erfolgreiche Veranderung hangt von der zielgerichteten Umsetzung pragmatischer Konzepte ab. Das Business Engineering liefert diese Konzepte. Das Buch zeigt, wie sie in der betrieblichen Realitat zu erfolgreichen Projekten fuhren. Die Nutzung der Informationstechnologie ist dabei das verbindende Element. Die von erfahrenen Praktikern des Business Engineering verfassten Beitrage drehen sich zum einen um technologiegetriebene Wertschopfungspotenziale und zum anderen um den methodischen Transformationsprozess zum Unternehmen des Informationszeitalters. Sie beschaftigen sich mit den zentralen Fragen des unternehmerischen Wandels: Wie andert sich die Geschaftslogik z.B. von Finanzdienstleistern, Industrieunternehmen oder Immobilienmanagement-Gesellschaften unterstutzt durch innovative Anwendungen? Welche Potenziale ergeben sich fur Supply-Chain-Management-Prozesse oder fur ein innovatives HR-Management? Welche Effekte ergeben sich in Netzwerken? Wie lassen sich die Erkenntnisse in KMU anwenden?

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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.

Der Einsatz von Software-Agenten zur Koordination wirtschaftlicher Prozesse und auf elektronischen Marktpl tzen ist Kernthema dieses Buches. Dabei werden Potenziale und Chancen, Anwendungen und Prototypen, aber auch Herausforderungen, Grenzen und Risiken der Agententechnologie f r den Einsatz aufgezeigt. Theoretische Grundlagen und Beispiele aus Projekten und deren Konzepte dienen als Basis f r die Realisierung eines eigenen agentenbasierten Markplatzes in Java. Im Vordergrund stehen daher praktische Ans tze zur Realisierung wirtschaftlicher Mechanismen und deren Implementierungen in eigenen Software-Agenten.
Die beigef gte CD enth lt eine eingeschr nkte Lizenzversion des kommerziellen Agentensystems "Living Agents Runtime System" sowie die im Buch beschriebenen Java-Klassen.

Maple is a powerful symbolic computation system that is widely used in universities around the world. This short introduction gives readers an insight into the rules that control how the system works, and how to understand, fix, and avoid common problems. Topics covered include algebra, calculus, linear algebra, graphics, programming, and procedures. Each chapter contains numerous illustrative examples, using mathematics that does not extend beyond first-year undergraduate material. Maple worksheets containing these examples are available for download from the author's personal website. The book is suitable for new users, but where advanced topics are central to understanding Maple they are tackled head-on. Many concepts which are absent from introductory books and manuals are described in detail. With this book, students, teachers and researchers will gain a solid understanding of Maple and how to use it to solve complex mathematical problems in a simple and efficient way.

Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this hands-on guide, you'll learn how to use the essential R tools you need to know to analyze data, including data types and programming concepts. The second half of Learning R shows you real data analysis in action by covering everything from importing data to publishing your results. Each chapter in the book includes a quiz on what you've learned, and concludes with exercises, most of which involve writing R code. Write a simple R program, and discover what the language can do Use data types such as vectors, arrays, lists, data frames, and strings Execute code conditionally or repeatedly with branches and loops Apply R add-on packages, and package your own work for others Learn how to clean data you import from a variety of sources Understand data through visualization and summary statistics Use statistical models to pass quantitative judgments about data and make predictions Learn what to do when things go wrong while writing data analysis code

This book covers the MATLAB syntax and the environment suitable for someone with no programming background. The first four chapters present information on basic MATLAB programming including computing terminology, MATLAB specific syntax and control structures, operators, arrays and matrices. The next cluster covers grouping data, working with files, making images, creating graphical user interfaces, experimenting with sound, and the debugging environment. The final three chapters contain case studies on using MATLAB and other tools and devices (e.g., Arduino, Linux, Git, Mex, etc.) important for basic programming knowledge. Companion files with code and 4 color figures are on the disc or available from the publisher. Features: Covers the MATLAB syntax and the environment, suitable for someone with no programming background Numerous examples, projects, and practical applications enhance understanding of subjects under discussion with over 100 MATLAB scripts and functions Includes companion files with code and 4 color figures from the text (on the disc or available from the publisher)

In today's competitive business environment, most companies realize that the better they can manage their customer relationships, the more successful they will become. Customer Relationship Management (CRM) software systems are key tools for companies to manage the customer-facing processes of their businesses. However, many companies have resisted implementing this most critical customer-oriented application due in large part to the lack of a single-point resource on implementing a CRM system. This book attempts to fill that gap. Implementing SAP (R) CRM will help technologists and managers come to grips with the vision, concept, and technology of CRM. It begins by laying out the groundwork for understanding CRM. It explains the concept and context of CRM and the tangible business benefits of CRM adoption. Demonstrating a professional approach to the evaluation and selection of SAP, it details the critical success factors (CSFs), patterns, and anti-patterns of a successful SAP CRM implementation. CRM implementations can add significant benefit to the company's bottom line only if the company first transforms itself into a customer-centric and customer-responsive enterprise. This book explains what it means to be a customer-centric and responsive enterprise, and provides a framework for business operations based on customer relationships, rather than the traditional four Ps (product, positioning, price, promotion). It further spells out business process reengineering (BPR) strategies to configure internal business processes and operations with SAP CRM to improve customer-facing strategies, services, and relationships.

Use Kanban to maximize efficiency, predictability, quality, and value With Kanban, every minute you spend on a software project can add value for customers. One book can help you achieve this goal: Agile Project Management with Kanban. Author Eric Brechner pioneered Kanban within the Xbox engineering team at Microsoft. Now he shows you exactly how to make it work for your team. Think of this book as "Kanban in a box": open it, read the quickstart guide, and you're up and running fast. As you gain experience, Brechner reveals powerful techniques for right-sizing teams, estimating, meeting deadlines, deploying components and services, adapting or evolving from Scrum or traditional Waterfall, and more. For every step of your journey, you'll find pragmatic advice, useful checklists, and actionable lessons. This truly is "Kanban in a box": all you need to deliver breakthrough value and quality. Use Kanban techniques to: Start delivering continuous value with your current team and project Master five quick steps for completing work backlogs Plan and staff new projects more effectively Minimize work in progress and quickly adjust to change Eliminate artificial meetings and prolonged stabilization Improve and enhance customer engagement Visualize workflow and fix revealed bottlenecks Drive quality upstream Integrate Kanban into large projects Optimize sustained engineering (contributed by James Waletzky) Expand Kanban beyond software development

The goals of this text are to develop the skills and an appreciation for the richness and versatility of modern time series analysis as a tool for analyzing dependent data. A useful feature of the presentation is the inclusion of nontrivial data sets illustrating the richness of potential applications to problems in the biological, physical, and social sciences as well as medicine. The text presents a balanced and comprehensive treatment of both time and frequency domain methods with an emphasis on data analysis. Numerous examples using data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and the analysis of economic and financial problems. The text can be used for a one semester/quarter introductory time series course where the prerequisites are an understanding of linear regression, basic calculus-based probability skills, and math skills at the high school level. All of the numerical examples use the R statistical package without assuming that the reader has previously used the software. Robert H. Shumway is Professor Emeritus of Statistics, University of California, Davis. He is a Fellow of the American Statistical Association and has won the American Statistical Association Award for Outstanding Statistical Application. He is the author of numerous texts and served on editorial boards such as the Journal of Forecasting and the Journal of the American Statistical Association. David S. Stoffer is Professor of Statistics, University of Pittsburgh. He is a Fellow of the American Statistical Association and has won the American Statistical Association Award for Outstanding Statistical Application. He is currently on the editorial boards of the Journal of Forecasting, the Annals of Statistical Mathematics, and the Journal of Time Series Analysis. He served as a Program Director in the Division of Mathematical Sciences at the National Science Foundation and as an Associate Editor for the Journal of the American Statistical Association and the Journal of Business & Economic Statistics.

It's no secret that cloud-based computing is the next big movement in IT, and Microsoft is right there in the market with Office 365a cloud-based productivity suite which includes a hosted, cloud-focused version of SharePoint 2010 SharePoint 2010 developers who have traditionally developed for on-premise environments will suddenly find themselves being asked to develop for the cloud. While there is a lot of overlap between cloud-based and traditional SharePoint development, there are also some important differences and considerations that must be taken into account as well. In particular, the proliferation of cloud-based solutions was a driving force behind certain new features in SharePoint 2010, like sandboxed solutions and the new client object model. As the devil is always in the details, Pro SharePoint 2010 Development for Office 365 helps you navigate the changes and develop compelling applications and solutions for SharePoint Online in Office 365. Authors Dave Milner, Bart McDonough, and Paul Stork bring to the table decades of experience in real-world development of solutions for customersexpertise that is the practical result of what works in real-world customer environments. This proven team will cover with you the architectural landscape that SharePoint in the cloud represents, discuss the steps in setting up a development environment, and cover multiple real-world development approaches, technologies, and considerations. What you'll learn Explicit advice for setting up development environments to work with Office 365 Coverage of possibilities for development including browser, SharePoint Designer, and Visual Studio Real-world development approaches In-depth coverage of sandboxed solutions including specific Office 365 considerations How to integrate InfoPath into an Office 365 SharePoint Online environment How to develop and deploy Silverlight applications within SharePoint Online Instructions for incorporating the most popular web development language JavaScriptand the most popular add-onjQuery Instructions for working with HTML5 and CSS3 with SharePoint Online Who this book is for

Online developers will findPro SharePoint 2010 Development for Office 365 most useful. Developers for SharePoint and .NET developers interested in SharePoint solutions for Office 365 will greatly benefit from a clear approach and road map to get into developing for SharePoint in an Office 365 environment. Online developers without a background in SharePoint will also greatly benefit from a concise approach to focusing on necessary concepts and components to get up to speed quickly in developing solutions for SharePoint Office 365. Table of Contents Getting Started with Office 365 and SharePoint Online SharePoint Online Development Overview Setting Up a Development Environment for SharePoint Online Basic Customization Using Only a Browser Taking It to the Next Level with SharePoint Designer InfoPath Forms and SharePoint Online Custom Development with Visual Studio SharePoint Designer Intro to Client-Side Development Client-Side Development with Silverlight Developing with jQuery, HTML5, and CSS3 Hybrid On-Premise/Online Solutions Office 365 Preview (Office 2013)

Microservices Security in Action teaches readers how to secure their microservices applications code and infrastructure. After a straightforward introduction to the challenges of microservices security, the book covers fundamentals to secure both the application perimeter and service-to-service communication. Following a hands-on example, readers explore how to deploy and secure microservices behind an API gateway as well as how to access microservices accessed by a single-page application (SPA). Key Features Key microservices security fundamentals Securing service-to-service communication with mTLS and JWT Deploying and securing microservices with Docker Using Kubernetes security Securing event-driven microservices Using the Istio Service Mesh For developers well-versed in microservices design principles who have a basic familiarity with Java. About the technology As microservices continue to change enterprise application systems, developers and architects must learn to integrate security into their design and implementation. Because microservices are created as a system of independent components, each a possible point of failure, they can multiply the security risk. Prabath Siriwardena is the vice president of security architecture at WSO2, a company that produces open source software, and has more than 12 years of experience in the identity management and security domain. Nuwan Dias is the director of API architecture at WSO2 and has worked in the software industry for more than 7 years, most of which he spent focusing on the API management domain. Both have helped build security designs for Fortune 500 companies including Boeing, Verizon, Nissan, HP, and GE.

Beginning R: An Introduction to Statistical Programming is a hands-on book showing how to use the R language, write and save R scripts, build and import data files, and write your own custom statistical functions. R is a powerful open-source implementation of the statistical language S, which was developed by AT&T. R has eclipsed S and the commercially-available S-Plus language, and has become the de facto standard for doing, teaching, and learning computational statistics. R is both an object-oriented language and a functional language that is easy to learn, easy to use, and completely free. A large community of dedicated R users and programmers provides an excellent source of R code, functions, and data sets. R is also becoming adopted into commercial tools such as Oracle Database. Your investment in learning R is sure to pay off in the long term as R continues to grow into the go to language for statistical exploration and research.* Covers the freely-available R language for statistics * Shows the use of R in specific uses case such as simulations, discrete probability solutions, one-way ANOVA analysis, and more * Takes a hands-on and example-based approach incorporating best practices with clear explanations of the statistics being done What you'll learn * Acquire and install R * Import and export data and scripts * Generate basic statistics and graphics * Program in R to write custom functions * Use R for interactive statistical explorations * Implement simulations and other advanced techniques Who this book is for Beginning R: An Introduction to Statistical Programming is an easy-to-read book that serves as an instruction manual and reference for working professionals, professors, and students who want to learn and use R for basic statistics. It is the perfect book for anyone needing a free, capable, and powerful tool for exploring statistics and automating their use.

A Strong Practical Focus on Applications and AlgorithmsComputational Statistics Handbook with MATLAB (R), Third Edition covers today's most commonly used techniques in computational statistics while maintaining the same philosophy and writing style of the bestselling previous editions. The text keeps theoretical concepts to a minimum, emphasizing the implementation of the methods. New to the Third EditionThis third edition is updated with the latest version of MATLAB and the corresponding version of the Statistics and Machine Learning Toolbox. It also incorporates new sections on the nearest neighbor classifier, support vector machines, model checking and regularization, partial least squares regression, and multivariate adaptive regression splines. Web ResourceThe authors include algorithmic descriptions of the procedures as well as examples that illustrate the use of algorithms in data analysis. The MATLAB code, examples, and data sets are available online.

Sharpening Your Advanced SAS (R) Skills presents sophisticated SAS programming techniques, procedures, and tools, such as Proc SQL, hash tables, and SAS Macro programming, for any industry. Drawing on his more than 20 years' experience of SAS programming in the pharmaceutical industry, the author provides a unique approach that empowers both advanced programmers who need a quick refresher and programmers interested in learning new techniques. The book helps you easily search for key points by summarizing and differentiating the syntax between similar SAS statements and options. Each chapter begins with an overview so you can quickly locate the detailed examples and syntax. The basic syntax, expected data, and descriptions are organized in summary tables to facilitate better memory recall. General rules list common points about similar statements or options. Real-world examples of SAS programs and code statements are line numbered with references, such as SAS papers and websites, for more detailed explanations. The text also includes end-of-chapter questions to reinforce your knowledge of the topics and prepare you for the advanced SAS certification exam. In addition, the author's website offers mindmaps and process flowcharts that connect concepts and relationships.

A Guide to Doing Statistics in Second Language Research Using SPSS and R, Second Edition is the only text available that demonstrates how to use SPSS and R as specifically related to applied linguistics and SLA research. This new edition is up-to-date with the most recent version of the SPSS software and now also includes coverage of R, a software program increasingly used by researchers in this field. Supported by a number of pedagogical features, including tip boxes and practice activities, and a wealth of screenshots, this book takes readers through each step of performing and understanding statistical research, covering the most commonly used tests in second language research, including t-tests, correlation, and ANOVA. A robust accompanying website covers additional tests of interest to students and researchers, taking them step-by-step through carrying out these tests themselves. In this comprehensive and hands-on volume, Jenifer Larson-Hall equips readers with a thorough understanding and the practical skills necessary to conducting and interpreting statisical research effectively using SPSS and R, ideal for graduate students and researchers in SLA, social sciences, and applied lingustics. For more information and materials, please visit www.routledge.com/cw/larson-hall.

An authoritative introduction to the latest comparative methods in evolutionary biology Phylogenetic comparative methods are a suite of statistical approaches that enable biologists to analyze and better understand the evolutionary tree of life, and shed vital new light on patterns of divergence and common ancestry among all species on Earth. This textbook shows how to carry out phylogenetic comparative analyses in the R statistical computing environment. Liam Revell and Luke Harmon provide an incisive conceptual overview of each method along with worked examples using real data and challenge problems that encourage students to learn by doing. By working through this book, students will gain a solid foundation in these methods and develop the skills they need to interpret patterns in the tree of life. Covers every major method of modern phylogenetic comparative analysis in R Explains the basics of R and discusses topics such as trait evolution, diversification, trait-dependent diversification, biogeography, and visualization Features a wealth of exercises and challenge problems Serves as an invaluable resource for students and researchers, with applications in ecology, evolution, anthropology, disease transmission, conservation biology, and a host of other areas Written by two of today's leading developers of phylogenetic comparative methods

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

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."

Effectively Access, Transform, Manipulate, Visualize, and Reason about Data and Computation Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving illustrates the details involved in solving real computational problems encountered in data analysis. It reveals the dynamic and iterative process by which data analysts approach a problem and reason about different ways of implementing solutions. The book's collection of projects, comprehensive sample solutions, and follow-up exercises encompass practical topics pertaining to data processing, including: Non-standard, complex data formats, such as robot logs and email messages Text processing and regular expressions Newer technologies, such as Web scraping, Web services, Keyhole Markup Language (KML), and Google Earth Statistical methods, such as classification trees, k-nearest neighbors, and naive Bayes Visualization and exploratory data analysis Relational databases and Structured Query Language (SQL) Simulation Algorithm implementation Large data and efficiency Suitable for self-study or as supplementary reading in a statistical computing course, the book enables instructors to incorporate interesting problems into their courses so that students gain valuable experience and data science skills. Students learn how to acquire and work with unstructured or semistructured data as well as how to narrow down and carefully frame the questions of interest about the data. Blending computational details with statistical and data analysis concepts, this book provides readers with an understanding of how professional data scientists think about daily computational tasks. It will improve readers' computational reasoning of real-world data analyses.

MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java. MATLAB Differential Equations introduces you to the MATLAB language with practical hands-on instructions and results, allowing you to quickly achieve your goals. In addition to giving an introduction to the MATLAB environment and MATLAB programming, this book provides all the material needed to work on differential equations using MATLAB. It includes techniques for solving ordinary and partial differential equations of various kinds, and systems of such equations, either symbolically or using numerical methods (Euler's method, Heun's method, the Taylor series method, the Runge-Kutta method,...). It also describes how to implement mathematical tools such as the Laplace transform, orthogonal polynomials, and special functions (Airy and Bessel functions), and find solutions of finite difference equations.

Instead of presenting the standard theoretical treatments that underlie the various numerical methods used by scientists and engineers, Using R for Numerical Analysis in Science and Engineering shows how to use R and its add-on packages to obtain numerical solutions to the complex mathematical problems commonly faced by scientists and engineers. This practical guide to the capabilities of R demonstrates Monte Carlo, stochastic, deterministic, and other numerical methods through an abundance of worked examples and code, covering the solution of systems of linear algebraic equations and nonlinear equations as well as ordinary differential equations and partial differential equations. It not only shows how to use R's powerful graphic tools to construct the types of plots most useful in scientific and engineering work, but also: Explains how to statistically analyze and fit data to linear and nonlinear models Explores numerical differentiation, integration, and optimization Describes how to find eigenvalues and eigenfunctions Discusses interpolation and curve fitting Considers the analysis of time series Using R for Numerical Analysis in Science and Engineering provides a solid introduction to the most useful numerical methods for scientific and engineering data analysis using R.

This book presents the statistical analysis of compositional data sets, i.e., data in percentages, proportions, concentrations, etc. The subject is covered from its grounding principles to the practical use in descriptive exploratory analysis, robust linear models and advanced multivariate statistical methods, including zeros and missing values, and paying special attention to data visualization and model display issues. Many illustrated examples and code chunks guide the reader into their modeling and interpretation. And, though the book primarily serves as a reference guide for the R package "compositions," it is also a general introductory text on Compositional Data Analysis. Awareness of their special characteristics spread in the Geosciences in the early sixties, but a strategy for properly dealing with them was not available until the works of Aitchison in the eighties. Since then, research has expanded our understanding of their theoretical principles and the potentials and limitations of their interpretation. This is the first comprehensive textbook addressing these issues, as well as their practical implications with regard to software. The book is intended for scientists interested in statistically analyzing their compositional data. The subject enjoys relatively broad awareness in the geosciences and environmental sciences, but the spectrum of recent applications also covers areas like medicine, official statistics, and economics. Readers should be familiar with basic univariate and multivariate statistics. Knowledge of R is recommended but not required, as the book is self-contained.

A guide to Microsoft Project that focuses on developing a successful project management strategy across the organization to drive better decisions

"Making Effective Business Decisions Using Microsoft Project" goes far beyond the basics of managing projects with Microsoft Project and how to set up and use the software. This unique guide is an indispensable resource for anyone who operates within a Project Management Operation (PMO) or is affected by the adoption of project management within an organization. Its focus is to provide practical and transitional information for those who are charged with making decisions and supporting corporate and strategic objectives, and who face cost and resource constraints.

Because more and more companies are aligning project management with their business strategies, the book not only provides guidance on using Microsoft Project and teaching project management skills, but also includes important information on measuring results and communicating with the executive branch. It also provides valuable guidance in using SharePoint Server for social networking and working within a team.

Clearly written and presented, the book: Covers work management using Microsoft Project at multiple levels within an organizationFocuses on using Microsoft Project 2010 to integrate and support overall organizational strategiesIncludes hundreds of graphics, screen shots, and annotations that make it the most accessible and usable guide available on the subject

"Making Effective Business Decisions Using Microsoft Projec"t is a valuable reference for project managers at all levels, and it sets a new standard for training manuals used by businesses that teach courses on project management using Microsoft Project.