Before use, standard ERP systems such as SAP R/3 need to be customized to meet the concrete requirements of the individual enterprise. This book provides an overview of the process models, methods, and tools offered by SAP and its partners to support this complex and time-consuming process. It begins by characterizing the foundations of the latest ERP systems from both a conceptual and technical viewpoint, whereby the most important components and functions of SAP R/3 are described. The main part of the book then goes on to present the current methods and tools for the R/3 implementation based on newer process models (roadmaps).

Past events have shed light on the vulnerability of mission-critical computer systems at highly sensitive levels. It has been demonstrated that common hackers can use tools and techniques downloaded from the Internet to attack government and commercial information systems. Although threats may come from mischief makers and pranksters, they are more likely to result from hackers working in concert for profit, hackers working under the protection of nation states, or malicious insiders. Securing an IT Organization through Governance, Risk Management, and Audit introduces two internationally recognized bodies of knowledge: Control Objectives for Information and Related Technology (COBIT 5) from a cybersecurity perspective and the NIST Framework for Improving Critical Infrastructure Cybersecurity (CSF). Emphasizing the processes directly related to governance, risk management, and audit, the book provides details of a cybersecurity framework (CSF), mapping each of the CSF steps and activities to the methods defined in COBIT 5. This method leverages operational risk understanding in a business context, allowing the information and communications technology (ICT) organization to convert high-level enterprise goals into manageable, specific goals rather than unintegrated checklist models. The real value of this methodology is to reduce the knowledge fog that frequently engulfs senior business management, and results in the false conclusion that overseeing security controls for information systems is not a leadership role or responsibility but a technical management task. By carefully reading, implementing, and practicing the techniques and methodologies outlined in this book, you can successfully implement a plan that increases security and lowers risk for you and your organization.

S+SPATIALSTATS is the first comprehensive, object-oriented package for the analysis of spatial data. Providing a whole new set of analysis tools, S+SPATIALSTATS was created specifically for the exploration and modeling of spatially correlated data. It can be used to analyze data arising in areas such as environmental, mining, and petroleum engineering, natural resources, geography, epidemiology, demography, and others where data is sampled spatially. This users manual provides the documentation for the S+SPATIALSTATS module.

Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process. This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner's reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book's R package. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics.

Mathematica (R) in the Laboratory is a hands-on guide which shows how to harness the power and flexibility of Mathematica in the control of data-acquisition equipment and the analysis of experimental data. It explains how to use Mathematica to import, manipulate, visualise and analyse data from existing files. The generation and export of test data are also covered. The control of laboratory equipment is dealt with in detail, including the use of Mathematica's MathLink (R) system in instrument control, data processing, and interfacing. Many practical examples are given, which can either be used directly or adapted to suit a particular application. The book sets out clearly how Mathematica can provide a truly unified data-handling environment, and will be invaluable to anyone who collects or analyses experimental data, including astronomers, biologists, chemists, mathematicians, geologists, physicists and engineers. The book is fully compatible with Mathematica 3.0.

COMPSTAT symposia have been held regularly since 1974 when they started in Vienna. This tradition has made COMPSTAT a major forum for the interplay of statistics and computer sciences with contributions from many well known scientists all over the world. The scientific programme of COMPSTAT '96 covers all aspects of this interplay, from user-experiences and evaluation of software through the development and implementation of new statistical ideas. All papers presented belong to one of the three following categories: - Statistical methods (preferable new ones) that require a substantial use of computing; - Computer environments, tools and software useful in statistics; - Applications of computational statistics in areas of substantial interest (environment, health, industry, biometrics, etc.).

Angesichts der tiefgreifenden A"nderungen der Transformationsprozesse im Finanzdienstleistungsbereich und in der betrieblichen Finanzwirtschaft sind innovative Financial-Management-LAsungen heute mehr denn je gefragt. Dieses Buch, welches sich gleichermaAen an EntscheidungstrAger und Fachexperten aus Praxis und Wissenschaft richtet, greift diesen Bedarf auf und prAsentiert richtungsweisende Forschungs- und Praxisarbeiten insbesondere in den Themenbereichen: Elektronische Finanzdienstleistungswirtschaft, Intermediation im elektronischen Wertpapierhandel/Online Brokerage, Risikomanagement und Kapitalallokation in Kreditinstituten und e-Insurance. Das Buch zeigt somit auf, welche vielversprechenden LAsungspotentiale durch den integrierten Einsatz informationstechnischer und finanzwirtschaftlicher Methoden und Konzepte erAffnet werden.

A greatly expanded and heavily revised second edition, this popular guide provides instructions and clear examples for running analyses of variance (ANOVA) and several other related statistical tests of significance with SPSS. No other guide offers the program statements required for the more advanced tests in analysis of variance. All of the programs in the book can be run using any version of SPSS, including versions 11 and 11.5. A table at the end of the preface indicates where each type of analysis (e.g., simple comparisons) can be found for each type of design (e.g., mixed two-factor design).
Providing comprehensive coverage of the basic and advanced topics in ANOVA, this is the only book available that provides extensive coverage of SPSS syntax, including the commands and subcommands that tell SPSS what to do, as well as the pull-down menu point-and-click method (PAC). Detailed explanation of the syntax, including what is necessary, desired, and optional helps ensure that users can validate the analysis being performed. The book features the output of each design along with a complete explanation of the related printout.
The new edition was reorganized to provide all analysis related to one design type in the same chapter. It now features expanded coverage of analysis of covariance (ANCOVA) and mixed designs, new chapters on designs with random factors, multivariate designs, syntax used in PAC, and all new examples of output with complete explanations. The new edition is accompanied by a CD-ROM with all of the book's data sets, as well as exercises for each chapter.
This book is ideal for readers familiar with the basic concepts of the ANOVA technique including both practicing researchers and data analysts, as well as advanced students learning analysis of variance.

Das erfolgreiche Fachbuch widmet sich der psychosozialen Dimension der Projektarbeit. Vor diesem Hintergrund werden alle Projektphasen beleuchtet. Schwerpunkte sind: Planung und Gestaltung des Projektbeginns, methodische Hinweise zur Teamarbeit, Regeln der Gesprachsfuhrung, Umgang mit Macht, Hierarchie und Widerstand im Rahmen der Projektarbeit, Partizipation, Gestaltung des Projektendes, Rolle und Anforderungsprofil des Projektleiters.
Fachlich kompetent und ubersichtlich gestaltet, gibt das Arbeitsbuch eine ebenso praxisgerechte wie breitgefacherte Hilfestellung fur Projektleiter und Fuhrungskrafte in den verschiedensten Bereichen. In der Neuauflage wurden die Entwicklungen in der Praxis berucksichtigt. Das Buch ist zu einem Klassiker der Projektarbeit geworden und wird in vielen Firmen und Seminaren als Lehrbuch eingesetzt."

The book, which contains over two hundred illustrations, is designed for use in school computer labs or with home computers, running the computer algebra system Maple, or its student version. It supports the interactive Maple worksheets, which the authors have developed and which are available free of charge via anonymous ftp (ftp.utirc.utoronto.ca (/pub/ednet/maths/maple)). The book addresses readers who are learning calculus at a pre-university level.

Der Vertrieb als Bindeglied zwischen Kunden und Unternehmen beeinflusst vor allem durch die Akquise ganz wesentlich den Unternehmenserfolg. Dabei ist der Vertrieb auf IT-Unterst tzung angewiesen. Die Gestaltung dieser Informationssysteme wird derzeit durch neue Trends herausgefordert. Dazu geh ren u. a. die Individualisierung und Hybridisierung des Leistungsangebots. Der Autor stellt in seiner ganzheitlichen Betrachtung neue Ans tze zur Gestaltung von Vertriebsinformationssystemen aus der Perspektive von Anbietern, Anwendern und Nutzern vor.

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.

Maple is a computer algebraic system with a fast-growing number of users in universities, schools and other institutions. Werner Burkhardt provides a detailed step-by-step introduction for all first-time users, enabling you to become familiar with the way Maple works, as quickly and easily as possible. Using as examples problems from many different aspects of mathematics, problem solving using Maple is fully described in this easy-to-follow tutorial text. Each chapter is self-contained, so you can easily select areas of your own special interest. There are some 'test yourself' problems at the end of each chapter to check your progress, with solutions provided at the end of the book.

This book is a collection of thirty invited papers, covering the important parts of a rapidly developing area like "computational statistics." All contributions supply information about a specialized topic in a tutorial and comprehensive style. Newest results and developments are discussed. Starting with the foundations of computational statistics, i.e. numerical reliability of software packages or construction principles for pseudorandom number generators, the volume includes design considerations on statistical programming languages and the basic issues of resampling techniques. Also covered are areas like design of experiments, graphical techniques, modelling and testing problems, a review of clustering algorithms, and concise discussions of regression trees or cognitive aspects of authoring systems.

Mathematica combines symbolic and numerical calculations, plots, graphics programming, list calculations and structured documentation into an interactive environment. This book covers the program and shows with practical examples how even more complex problems can be solved with just a few commands.

From the reviews: "A valuable introductory textbook on Mathematica and is very useful to scientists and engineers who use Mathematica in their work." -- ZENTRALBLATT MATH

This book assembles papers which were presented at the biennial sympo sium in Computational Statistics held und er the a uspices of the International Association for Statistical Computing (IASC), a section of ISI, the Interna tional Statistical Institute. This symposium named COMPSTAT '94 was organized by the Statistical Institutes of the University of Vienna and the University of Technology of Vienna, Austria. The series of COMPSTAT Symposia started 1974 in Vienna. Mean while they took place every other year in Berlin (Germany, 1976), Leiden (The Netherlands, 1978), Edinburgh (Great Britain, 1980), Toulouse (France, 1982), Prague (Czechoslovakia, 1984), Rom (Italy, 1986), Copenhagen (Den mark, 1988), Dubrovnik (Yugoslavia, 1990) and Neuchatel (Switzerland, 1992). This year we are celebrating the 20th anniversary in Vienna, Austria. It has obviously been observed a movement from "traditional" computa tional statistics with emphasis on methods which produce results quickly and reliably, to computationally intensive methods like resampling procedures, Bayesian methods, dynamic graphics, to very recent areas like neural net works, accentuation on spatial statistics, huge data sets, analysis strategies, etc. For the organization of the symposium, new guidelines worked out by the IASC in written form were in effect this time. The goal was to refresh somehow the spirit of the start of COMPSTAT '74, keep the tradition of the series and ensure a certain continuity in the sequence of biannual meetings."

The emphasis of the book is given in how to construct different types of solutions (exact, approximate analytical, numerical, graphical) of numerous nonlinear PDEs correctly, easily, and quickly. The reader can learn a wide variety of techniques and solve numerous nonlinear PDEs included and many other differential equations, simplifying and transforming the equations and solutions, arbitrary functions and parameters, presented in the book). Numerous comparisons and relationships between various types of solutions, different methods and approaches are provided, the results obtained in Maple and Mathematica, facilitates a deeper understanding of the subject. Among a big number of CAS, we choose the two systems, Maple and Mathematica, that are used worldwide by students, research mathematicians, scientists, and engineers. As in the our previous books, we propose the idea to use in parallel both systems, Maple and Mathematica, since in many research problems frequently it is required to compare independent results obtained by using different computer algebra systems, Maple and/or Mathematica, at all stages of the solution process. One of the main points (related to CAS) is based on the implementation of a whole solution method (e.g. starting from an analytical derivation of exact governing equations, constructing discretizations and analytical formulas of a numerical method, performing numerical procedure, obtaining various visualizations, and comparing the numerical solution obtained with other types of solutions considered in the book, e.g. with asymptotic solution).

The analysis of time series data is an important aspect of data analysis across a wide range of disciplines, including statistics, mathematics, business, engineering, and the natural and social sciences. This package provides both an introduction to time series analysis and an easy-to-use version of a well-known time series computing package called Interactive Time Series Modelling. The programs in the package are intended as a supplement to the text Time Series: Theory and Methods, 2nd edition, also by Peter J. Brockwell and Richard A. Davis. Many researchers and professionals will appreciate this straightforward approach enabling them to run desk-top analyses of their time series data. Amongst the many facilities available are tools for: ARIMA modelling, smoothing, spectral estimation, multivariate autoregressive modelling, transfer-function modelling, forecasting, and long-memory modelling. This version is designed to run under Microsoft Windows 3.1 or later. It comes with two diskettes: one suitable for less powerful machines (IBM PC 286 or later with 540K available RAM and 1.1 MB of hard disk space) and one for more powerful machines (IBM PC 386 or later with 8MB of RAM and 2.6 MB of hard disk space available).

Now in its second edition, this textbook provides an introduction to Python and its use for statistical data analysis. It covers common statistical tests for continuous, discrete and categorical data, as well as linear regression analysis and topics from survival analysis and Bayesian statistics. For this new edition, the introductory chapters on Python, data input and visualization have been reworked and updated. The chapter on experimental design has been expanded, and programs for the determination of confidence intervals commonly used in quality control have been introduced. The book also features a new chapter on finding patterns in data, including time series. A new appendix describes useful programming tools, such as testing tools, code repositories, and GUIs. The provided working code for Python solutions, together with easy-to-follow examples, will reinforce the reader's immediate understanding of the topic. Accompanying data sets and Python programs are also available online. With recent advances in the Python ecosystem, Python has become a popular language for scientific computing, offering a powerful environment for statistical data analysis. With examples drawn mainly from the life and medical sciences, this book is intended primarily for masters and PhD students. As it provides the required statistics background, the book can also be used by anyone who wants to perform a statistical data analysis.

Design and Analysis of Experiments with R presents a unified treatment of experimental designs and design concepts commonly used in practice. It connects the objectives of research to the type of experimental design required, describes the process of creating the design and collecting the data, shows how to perform the proper analysis of the data, and illustrates the interpretation of results. Drawing on his many years of working in the pharmaceutical, agricultural, industrial chemicals, and machinery industries, the author teaches students how to: Make an appropriate design choice based on the objectives of a research project Create a design and perform an experiment Interpret the results of computer data analysis The book emphasizes the connection among the experimental units, the way treatments are randomized to experimental units, and the proper error term for data analysis. R code is used to create and analyze all the example experiments. The code examples from the text are available for download on the author's website, enabling students to duplicate all the designs and data analysis. Intended for a one-semester or two-quarter course on experimental design, this text covers classical ideas in experimental design as well as the latest research topics. It gives students practical guidance on using R to analyze experimental data.

Sie treffen taglich Entscheidungen. Doch selten ist eine so komplex wie die Auswahl einer Software. Gute Vorbereitung ist daher umso wichtiger. Sie wollen die notwendige Qualitat des Lasten- bzw. Pflichtenheftes sicherstellen. Sie benotigen Zeit fur Marktanalyse und Ausschreibung. ePAVOS ist hierfur die Methode der Wahl: effizient, nachvollziehbar und zeitsparend. Sie deckt Compliance und andere externe Anforderungen ab. Sie macht das umfangreiche Vertragswerk transparent und gewahrleistet die Kontrolle uber Ihr Gesamtprojekt. Drei Experten liefern das Wichtigste aus Praxis, Theorie und Recht."

Master the tools of MATLAB through hands-on examplesShows How to Solve Math Problems Using MATLAB The mathematical software MATLAB (R) integrates computation, visualization, and programming to produce a powerful tool for a number of different tasks in mathematics. Focusing on the MATLAB toolboxes especially dedicated to science, finance, and engineering, MATLAB (R) with Applications to Engineering, Physics and Finance explains how to perform complex mathematical tasks with relatively simple programs. This versatile book is accessible enough for novices and users with only a fundamental knowledge of MATLAB, yet covers many sophisticated concepts to make it helpful for experienced users as well. The author first introduces the basics of MATLAB, describing simple functions such as differentiation, integration, and plotting. He then addresses advanced topics, including programming, producing executables, publishing results directly from MATLAB programs, and creating graphical user interfaces. The text also presents examples of Simulink (R) that highlight the advantages of using this software package for system modeling and simulation. The applications-dedicated chapters at the end of the book explore the use of MATLAB in digital signal processing, chemical and food engineering, astronomy, optics, financial derivatives, and much more.

These lecture notes provide a rapid, accessible introduction to Bayesian statistical methods. The course covers the fundamental philosophy and principles of Bayesian inference, including the reasoning behind the prior/likelihood model construction synonymous with Bayesian methods, through to advanced topics such as nonparametrics, Gaussian processes and latent factor models. These advanced modelling techniques can easily be applied using computer code samples written in Python and Stan which are integrated into the main text. Importantly, the reader will learn methods for assessing model fit, and to choose between rival modelling approaches.

Die Grenzen zwischen Sach- und Dienstleistung verschwimmen zunehmend - Produkte sind in der Regel hybrid. Sie sind als kundenorientierte Problemloesungen zu interpretieren, die durch das Schnuren von Leistungsbundeln aus Sach- und Dienstleistungskomponenten entstehen. UEber die Wettbewerbsvorteile und den oekonomischen Nutzen von hybriden Produkten herrscht weitgehend Einigkeit. Dennoch existieren kaum Ansatze zur integrierten Entwicklung von Sach- und Dienstleistungen. Die Tatsache, dass der wirtschaftliche Erfolg eines Leistungsbundels massgeblich von dessen Konzeption und kundenindividueller Gestaltung abhangt, wird damit vernachlassigt. In diesem Band werden neue Methoden zur Gestaltung hybrider Produkte vorgestellt. Dabei werden sowohl aktuelle Problemstellungen und Loesungsansatze als auch zukunftige Entwicklungsperspektiven betrachtet. Die einzelnen Kapitel fokussieren einerseits die Produktion und den Absatz hybrider Produkte und andererseits Informationssysteme, welche die Produktion und den Absatz hybrider Produkte unterstutzen. Es wird dem Grundgedanken gefolgt, dass die Erfullung einer Kundenanforderung nicht von vorneherein entweder an eine Sach- oder eine Dienstleistungskomponente geknupft ist - diese Zuordnung soll sich erst wahrend des Entwicklungsprozesses eines hybriden Produkts ergeben. Als "roter Faden" dient ein durchgangiges Fallbeispiel aus der technischen Gebrauchsguterbranche, bei dem die Nutzung mobiler Endgerate zu Verbesserungen in der Erbringung technischer Kundendienstleistungen fuhrt.

Learn how to program by diving into the R language, and then use your newfound skills to solve practical data science problems. With this book, you'll learn how to load data, assemble and disassemble data objects, navigate R's environment system, write your own functions, and use all of R's programming tools. RStudio Master Instructor Garrett Grolemund not only teaches you how to program, but also shows you how to get more from R than just visualizing and modeling data. You'll gain valuable programming skills and support your work as a data scientist at the same time. Work hands-on with three practical data analysis projects based on casino games Store, retrieve, and change data values in your computer's memory Write programs and simulations that outperform those written by typical R users Use R programming tools such as if else statements, for loops, and S3 classes Learn how to write lightning-fast vectorized R code Take advantage of R's package system and debugging tools Practice and apply R programming concepts as you learn them