Data Presentation with SPSS Explained provides students with all the information they need to conduct small scale analysis of research projects using SPSS and present their results appropriately in their reports. Quantitative data can be collected in the form of a questionnaire, survey or experimental study. This book focuses on presenting this data clearly, in the form of tables and graphs, along with creating basic summary statistics. Data Presentation with SPSS Explained uses an example survey that is clearly explained step-by-step throughout the book. This allows readers to follow the procedures, and easily apply each step in the process to their own research and findings. No prior knowledge of statistics or SPSS is assumed, and everything in the book is carefully explained in a helpful and user-friendly way using worked examples. This book is the perfect companion for students from a range of disciplines including psychology, business, communication, education, health, humanities, marketing and nursing - many of whom are unaware that this extremely helpful program is available at their institution for their use.

*When R creates copies, and how it affects memory usage and code performance *Everything you could ever want to know about functions *The differences between calling and exiting handlers *How to employ functional programming to solve modular tasks *The motivation, mechanics, usage, and limitations of R's highly pragmatic S3 OO system *The R6 OO system, which is more like OO programming in other languages *The rules that R uses to parse and evaluate expressions *How to use metaprogramming to generate HTML or LaTeX with elegant R code *How to identify and resolve performance bottlenecks

Konzentrationstendenzen, Globalisierung und gut informierte Kunden sind Belege f r den harten Wettbewerb, in dem sich Handelsunternehmen befinden. Um in diesem Wettbewerb zu bestehen, ben tigen H ndler flexibel an die jeweilige Unternehmensstruktur anpassbare Informations- und Kommunikationssysteme, die die operativen Abl ufe, Beschaffung, Lagerung und Distribution und die betriebswirtschaftlich-administrativen Aufgaben der Buchhaltung, Kostenrechnung und Personalwirtschaft unterst tzen und aussagekr ftige Auswertungssysteme umfassen. Dar ber hinaus sind Informations- und Planungssysteme zur Unterst tzung von Marketing und Management heute kritischer Erfolgsfaktor. Das Buch stellt die Architektur von Handelsinformationssystemen am Beispiel des SAP Retail-Systems dar. Es zeigt auf, wie modernes Handelsmanagement durch Einsatz integrierter Standardsoftware realisiert werden kann.

For problems that require extensive computation, a C++ program can race through billions of examples faster than most other computing choices. C++ enables mathematicians of virtually any discipline to create programs to meet their needs quickly, and is available on most computer systems at no cost. C++ for Mathematicians: An Introduction for Students and Professionals accentuates C++ concepts that are most valuable for pure and applied mathematical research. This is the first book available on C++ programming that is written specifically for a mathematical audience; it omits the language's more obscure features in favor of the aspects of greatest utility for mathematical work. The author explains how to use C++ to formulate conjectures, create images and diagrams, verify proofs, build mathematical structures, and explore myriad examples. Emphasizing the essential role of practice as part of the learning process, the book is ideally designed for undergraduate coursework as well as self-study. Each chapter provides many problems and solutions which complement the text and enable you to learn quickly how to apply them to your own problems. Accompanying downloadable resources provide all numbered programs so that readers can easily use or adapt the code as needed. Presenting clear explanations and examples from the world of mathematics that develop concepts from the ground up, C++ for Mathematicians can be used again and again as a resource for applying C++ to problems that range from the basic to the complex.

Anwendbarkeit des Mediendienstestaatsvertrages oder handelt es sich um Rund funk mit der Folge der Anwendung der Rundfunkgesetzes der Lander? Der zweite Abschnitt behandelt den "Rechtsverkehr im Internet'. Zunachst wird in Kapitel 3 der "Vertragsschluss im Internet" nach deutschem Recht erfasst. In Kapitel 15 ("Electronic Commerce im Internet") und 16 ("Rechtsfragen des In ternet-Vertriebs von Versicherungsdienstleistungen" werden die europaischen Re gelungen - insbesondere aus der Sicht des Verbraucherschutzes - hierzu bereits an tizipiert. Ferner gilt es zu berucksichtigen, dass der Geschaftsverkehr uber das In ternet eine zusatzliche Flankierung durch die Moglichkeit der Abwicklung von "Zahlungsverkehr im Internet' erhalt. Die zahlreichen rechtlichen Probleme, die mit der Verwendung von Cybermoney etc. auftauchen, werden in Kapitel 4 aufge griffen. Das Kapitel 5 behandelt sodann mit dem Thema, Rechtssicherheit im digitalen Rechtsverkehr'' einen zentralen Gesichtspunkt des Rechtsverkehrs. Dabei wird neben dem deutschen Signaturgesetz samt Signaturverordnung auch die eu ropaische Rechtsentwicklung berucksichtigt. Der dritte Abschnitt umfasst "die Rechtsstellung der Beteiligten." Zentral hier fiir ist die Frage nach der Verantwortlichkeit die sowohl den Diensteanbieter Kapi tel 6) als auch den Netzbelreiber (Kapitel 7) betrifft. Die strafrechtliche Perspek tive wird gesondert in Kapitel 18 aufgenommen. Eine in der Praxis immer haufi ger auftretende Frage gilt der Einordnung der "Vertragsgestaltung zwischen den Beteiligten" woruber Kapitel 8 Auskunft gibt."

Das Buch thematisiert den deutschen Markt f r TV-Kabelnetze in seiner Entwicklung vom Monopol zum Wettbewerb. Schwerpunkt der Betrachtung bilden die auf diesem Markt handelnden Akteure mit ihren unterschiedlichen Interessen und Strategien. So wird die Bedeutung des ehemaligen Staatsmonopolisten "Deutsche Telekom" f r die Entwicklung dieses Marktes ebenso herausgestellt und kritisch analysiert, wie die der deutschen und internationalen Kabelnetzbetreiber. Zentrale Themen des Buches sind: Bedeutung von Wettbewerb und Deregulierung f r den deutschen TV-Kabelmarkt, Wettbewerbssituation und Potenziale privater Kabelnetzbetreiber. Diese Aspekte sind eingebettet in die Darstellung und Analyse der ordnungspolitischen Rahmenbedingungen des TV-Kabelmarktes sowie der hieraus resultierenden, innovativen Wettbewerbsbedingungen. Das Buch bietet einen im deutschsprachigen Raum einmaligen Einblick.

Die Versorgung des Managements mit validen und aktuellen Informationen zur Wahrnehmung der Fuhrungs-, Steuerungs- und Kontrollaufgaben ist zu einer der wichtigsten Herausforderungen fur die Wirtschaftsinformatik geworden. Die Forderung nach integrierten Informations- und Kommunikationssystemen, welche aus unternehmensinternen und unternehmensexternen Datenquellen entsch- dungsrelevante Informationen mit einem hohen Mass an Automatisierung zus- mentragen und aufbereiten, begleitet die IT-Abteilungen seit vielen Jahren. Unter wechselnden Schlagworten wurden Konzepte zur Informationsversorgung des Managements propagiert, deren Einsatztauglichkeit aber haufig hinter den Erw- tungen zuruckblieb. Dennoch haben sich in den 90er Jahren in fast allen Unt- nehmungen Data-Warehouse-Losungen durchsetzen konnen, da diese nachwe- lich zu einer erhohten Qualitat und Aktualitat der Informationsbereitstellung fur Fach- und Fuhrungskrafte beitragen. Unter dem Begriff Business Intelligence" werden derzeit dialogfahige Informationssysteme mit hohem Verfugungsgrad, intuitiver Nutzbarkeit und analytischer Funktionsvielfalt verbreitet, die auf dem bereinigten Datenbestand eines derartigen Data Warehouse aufsetzen. Der SAP AG gelang es, nach spatem Entwicklungsstart in diesem Marktsegment mit dem Produkt SAP Business Information Warehouse (SAP BW )" einen fuhrenden Platz einzunehmen. Als Plattform fur die Sammlung von betriebswi- schaftlichen Grunddaten ist das SAP BW ein wesentlicher Bestandteil der Anwendungsarchitektur im Gesamtkonzept der SAP-Produkte geworden. Samt- che Systemkomponenten, welche Planungs-, Steuerungs- und Berichtsaufgaben unterstutzen, beziehen jetzt und zukunftig ihre Daten aus dem SAP BW . Dies gilt sowohl fur das Produkt SAP Strategic Enterprise Management (SAP SEM )" als auch fur die Softwarekomponente SAP Advanced Planner and Optimizer (SAP APO ).""

This book presents strategies for analyzing qualitative and mixed methods data with MAXQDA software, and provides guidance on implementing a variety of research methods and approaches, e.g. grounded theory, discourse analysis and qualitative content analysis, using the software. In addition, it explains specific topics, such as transcription, building a coding frame, visualization, analysis of videos, concept maps, group comparisons and the creation of literature reviews. The book is intended for masters and PhD students as well as researchers and practitioners dealing with qualitative data in various disciplines, including the educational and social sciences, psychology, public health, business or economics.

Do you want to create data analysis reports without writing a line of code? This book introduces SAS Studio, a free data science web browser-based product for educational and non-commercial purposes. The power of SAS Studio comes from its visual point-and-click user interface that generates SAS code. It is easier to learn SAS Studio than to learn R and Python to accomplish data cleaning, statistics, and visualization tasks. The book includes a case study about analyzing the data required for predicting the results of presidential elections in the state of Maine for 2016 and 2020. In addition to the presidential elections, the book provides real-life examples including analyzing stocks, oil and gold prices, crime, marketing, and healthcare. You will see data science in action and how easy it is to perform complicated tasks and visualizations in SAS Studio. You will learn, step-by-step, how to do visualizations, including maps. In most cases, you will not need a line of code as you work with the SAS Studio graphical user interface. The book includes explanations of the code that SAS Studio generates automatically. You will learn how to edit this code to perform more complicated advanced tasks. The book introduces you to multiple SAS products such as SAS Viya, SAS Analytics, and SAS Visual Statistics. What You Will Learn Become familiar with SAS Studio IDE Understand essential visualizations Know the fundamental statistical analysis required in most data science and analytics reports Clean the most common data set problems Use linear progression for data prediction Write programs in SAS Get introduced to SAS-Viya, which is more potent than SAS studio Who This Book Is For A general audience of people who are new to data science, students, and data analysts and scientists who are experienced but new to SAS. No programming or in-depth statistics knowledge is needed.

A Tour of Data Science: Learn R and Python in Parallel covers the fundamentals of data science, including programming, statistics, optimization, and machine learning in a single short book. It does not cover everything, but rather, teaches the key concepts and topics in Data Science. It also covers two of the most popular programming languages used in Data Science, R and Python, in one source. Key features: Allows you to learn R and Python in parallel Cover statistics, programming, optimization and predictive modelling, and the popular data manipulation tools - data.table and pandas Provides a concise and accessible presentation Includes machine learning algorithms implemented from scratch, linear regression, lasso, ridge, logistic regression, gradient boosting trees, etc. Appealing to data scientists, statisticians, quantitative analysts, and others who want to learn programming with R and Python from a data science perspective.

Clinical Data Quality Checks for CDISC Compliance using SAS is the first book focused on identifying and correcting data quality and CDISC compliance issues with real-world innovative SAS programming techniques such as Proc SQL, metadata and macro programming. Learn to master Proc SQL's subqueries and summary functions for multi-tasking process. Drawing on his more than 25 years' experience in the pharmaceutical industry, the author provides a unique approach that empowers SAS programmers to take control of data quality and CDISC compliance. This book helps you create a system of SDTM and ADaM checks that can be tracked for continuous improvement. How often have you encountered issues such as missing required variables, duplicate records, invalid derived variables and invalid sequence of two dates? With the SAS programming techniques introduced in this book, you can start to monitor these and more complex data and CDISC compliance issues. With increased standardization in SDTM and ADaM specifications and data values, codelist dictionaries can be created for better organization, planning and maintenance. This book includes a SAS program to create excel files containing unique values from all SDTM and ADaM variables as columns. In addition, another SAS program compares SDTM and ADaM codelist dictionaries with codelists from define.xml specifications. Having tools to automate this process greatly saves time from doing it manually. Features SDTMs and ADaMs Vitals SDTMs and ADaMs Data CDISC Specifications Compliance CDISC Data Compliance Protocol Compliance Codelist Dictionary Compliance

IT-Projekte mussen durch Projektvertrage auf allen Stufen gezielt gesteuert und kontrolliert werden, um erfolgreich zu sein. Der Autor geht auf die Verantwortlichkeit des Managements fur die Projektfuhrung ein und erlautert die aktuellen Normvorgaben fur IT-Projekte aus ISO 20.000 und ITIL. Behandelt werden auch Outsourcing und ASP sowie IT-Security, gewissermassen Dauerprojekte, ebenso die Sanierung von Projekten und die Anwenderrechte bei Anbieterinsolvenz.

Ausfuhrliche Checklisten fur CIOs und Geschaftsleitungen sollen schliesslich aus deren Blickwinkel die Projektkontrolle erleichtern. In dieser Themenkombination gibt es am Buchmarkt gegenwartig keine gleichartige Darstellung."

This compact course is written for the mathematically literate reader who wants to learn to analyze data in a principled fashion. The language of mathematics enables clear exposition that can go quite deep, quite quickly, and naturally supports an axiomatic and inductive approach to data analysis. Starting with a good grounding in probability, the reader moves to statistical inference via topics of great practical importance - simulation and sampling, as well as experimental design and data collection - that are typically displaced from introductory accounts. The core of the book then covers both standard methods and such advanced topics as multiple testing, meta-analysis, and causal inference.

Mathematical Statistics with Applications in R, Third Edition, offers a modern calculus-based theoretical introduction to mathematical statistics and applications. The book covers many modern statistical computational and simulation concepts that are not covered in other texts, such as the Jackknife, bootstrap methods, the EM algorithms, and Markov chain Monte Carlo (MCMC) methods, such as the Metropolis algorithm, Metropolis-Hastings algorithm and the Gibbs sampler. By combining discussion on the theory of statistics with a wealth of real-world applications, the book helps students to approach statistical problem-solving in a logical manner. Step-by-step procedure to solve real problems make the topics very accessible.

Die schnelle und effiziente Realisierung innovativer Dienstleistungen stellt zunehmend einen Erfolgsfaktor fur die Wettbewerbsfahigkeit von Dienstleistungsunternehmen dar. Dienstleistungen werden in der Praxis jedoch oft "ad hoc," d.h. ohne systematische Vorgehensweise, entwickelt. Das Konzept des "Service Engineering" beschreibt Vorgehensweisen, Methoden und Werkzeugunterstutzung fur die systematische Planung, Entwicklung und Realisierung innovativer Dienstleistungen. Ziel des Buches ist es, Wissenschaftlern und Praktikern gleichermassen einen Uberblick uber den aktuellen Kenntnisstand wie auch uber zukunftige Tendenzen im Service Engineering zu geben. Die Beitrage wurden fur die Neuauflage aktualisiert, zusatzlich wurden Beitrage namhafter Autoren aus Wissenschaft und Praxis in wichtigen, aber bislang unbesetzten Themenfeldern aufgenommen. "

Examine the latest developments in online business with cutting-edge coverage, real examples, actual business cases, and hands-on applications found in the market-leading ELECTRONIC COMMERCE, 12E. With comprehensive coverage of emerging strategies and today's most important technologies, this popular book equips you with a solid understanding of the dynamics of this fast-paced industry. The new edition offers thorough discussions of e-commerce growth in the rapidly-developing economies of China, India, and Brazil. You also examine key topics, such as social media and online marketing strategies, technology-enabled outsourcing, and online payment processing systems. New intriguing "Learning From Failure" segments help you draw important lessons from the experiences of actual companies as you review real-world e-commerce practices in action.

Chunyan Li is a course instructor with many years of experience in teaching about time series analysis. His book is essential for students and researchers in oceanography and other subjects in the Earth sciences, looking for a complete coverage of the theory and practice of time series data analysis using MATLAB. This textbook covers the topic's core theory in depth, and provides numerous instructional examples, many drawn directly from the author's own teaching experience, using data files, examples, and exercises. The book explores many concepts, including time; distance on Earth; wind, current, and wave data formats; finding a subset of ship-based data along planned or random transects; error propagation; Taylor series expansion for error estimates; the least squares method; base functions and linear independence of base functions; tidal harmonic analysis; Fourier series and the generalized Fourier transform; filtering techniques: sampling theorems: finite sampling effects; wavelet analysis; and EOF analysis.

Das Verstandnis des einstigen Modewortes "E-Commerce" hat sich verschoben. Nicht langer stehen vage Prognosen im Mittelpunkt. Der vorliegende Band unterzieht die Potenziale des Technologieeinsatzes und ihrer nachhaltigen oekonomischen Verwertung einer realistischen Analyse. Namhafte Wissenschaftler und Praktiker geben einen UEberblick uber die aktuelle Forschung sowie Anwendungen in den Bereichen Netze, Markte, Dienste und Technologien. Dabei werden die Moeglichkeiten der Umsetzung innovativer wissenschaftlicher Ansatze in die Praxis, aber auch des Transfers praxisrelevanter Problemstellungen in die Forschungslabors sowohl aus oekonomischer als auch aus informationstechnischer Sicht beleuchtet.

An accessible primer on how to create effective graphics from data This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way. Data Visualization builds the reader's expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective "small multiple" plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible. Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings. Provides hands-on instruction using R and ggplot2 Shows how the "tidyverse" of data analysis tools makes working with R easier and more consistent Includes a library of data sets, code, and functions

Presents the main ideas of computer-intensive statistical methods Gives the algorithms for all the methods Uses various plots and illustrations for explaining the main ideas Features the theoretical backgrounds of the main methods. Includes R codes for the methods and examples

This book presents two new decomposition methods to decompose a time series in intrinsic components of low and high frequencies. The methods are based on Singular Value Decomposition (SVD) of a Hankel matrix (HSVD). The proposed decomposition is used to improve the accuracy of linear and nonlinear auto-regressive models. Linear Auto-regressive models (AR, ARMA and ARIMA) and Auto-regressive Neural Networks (ANNs) have been found insufficient because of the highly complicated nature of some time series. Hybrid models are a recent solution to deal with non-stationary processes which combine pre-processing techniques with conventional forecasters, some pre-processing techniques broadly implemented are Singular Spectrum Analysis (SSA) and Stationary Wavelet Transform (SWT). Although the flexibility of SSA and SWT allows their usage in a wide range of forecast problems, there is a lack of standard methods to select their parameters. The proposed decomposition HSVD and Multilevel SVD are described in detail through time series coming from the transport and fishery sectors. Further, for comparison purposes, it is evaluated the forecast accuracy reached by SSA and SWT, both jointly with AR-based models and ANNs.

Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today's most popular machine learning methods. This book serves as a practitioner's guide to the machine learning process and is meant to help the reader learn to apply the machine learning stack within R, which includes using various R packages such as glmnet, h2o, ranger, xgboost, keras, and others to effectively model and gain insight from their data. The book favors a hands-on approach, providing an intuitive understanding of machine learning concepts through concrete examples and just a little bit of theory. Throughout this book, the reader will be exposed to the entire machine learning process including feature engineering, resampling, hyperparameter tuning, model evaluation, and interpretation. The reader will be exposed to powerful algorithms such as regularized regression, random forests, gradient boosting machines, deep learning, generalized low rank models, and more! By favoring a hands-on approach and using real word data, the reader will gain an intuitive understanding of the architectures and engines that drive these algorithms and packages, understand when and how to tune the various hyperparameters, and be able to interpret model results. By the end of this book, the reader should have a firm grasp of R's machine learning stack and be able to implement a systematic approach for producing high quality modeling results. Features: * Offers a practical and applied introduction to the most popular machine learning methods. * Topics covered include feature engineering, resampling, deep learning and more. * Uses a hands-on approach and real world data.

Create project plans that make the most of your money and time

Get your projects on track, manage resources, and share information online

Project 2007 helps you keep your projects on track by providing sophisticated tools for building task outlines and important timing relationships; efficiently assigning people, cost, and material resources; and keeping everyone and everything on schedule. Get an overview of the benefits of Project Server and Project Web Access for communicating with your team and managing your project online.

All this on the bonus CD-ROMTools for creating enhanced graphics and reportsStrategic planning and brainstorming toolsProject add-ons that improve your time reporting and tracking capabilitiesFor details and complete system requirements, see the CD-ROM appendix.

Discover how toEmploy the powerful new features of Project 2007Track down problems with Task DriversExplore Project's new Visual ReportsGet tips for saving time and money on your projects

Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.

Die Evolution grosser Software-Systeme halt fur viele Unternehmen immer wieder UEberraschungen bereit. Software-Konfigurationsmanagement dient dazu, Zeit und Aufwand bei der Entwicklung und Pflege langlebiger komplexer Softwaresysteme zu reduzieren und die Software-Evolution beherrschbar zu machen. Das Buch beschreibt die Einfuhrung und effiziente Anwendung von Konfigurationsmanagement und stellt die Integration in das AEnderungsmanagement ausfuhrlich dar.

This textbook on practical data analytics unites fundamental principles, algorithms, and data. Algorithms are the keystone of data analytics and the focal point of this textbook. Clear and intuitive explanations of the mathematical and statistical foundations make the algorithms transparent. But practical data analytics requires more than just the foundations. Problems and data are enormously variable and only the most elementary of algorithms can be used without modification. Programming fluency and experience with real and challenging data is indispensable and so the reader is immersed in Python and R and real data analysis. By the end of the book, the reader will have gained the ability to adapt algorithms to new problems and carry out innovative analyses. This book has three parts:(a) Data Reduction: Begins with the concepts of data reduction, data maps, and information extraction. The second chapter introduces associative statistics, the mathematical foundation of scalable algorithms and distributed computing. Practical aspects of distributed computing is the subject of the Hadoop and MapReduce chapter.(b) Extracting Information from Data: Linear regression and data visualization are the principal topics of Part II. The authors dedicate a chapter to the critical domain of Healthcare Analytics for an extended example of practical data analytics. The algorithms and analytics will be of much interest to practitioners interested in utilizing the large and unwieldly data sets of the Centers for Disease Control and Prevention's Behavioral Risk Factor Surveillance System.(c) Predictive Analytics Two foundational and widely used algorithms, k-nearest neighbors and naive Bayes, are developed in detail. A chapter is dedicated to forecasting. The last chapter focuses on streaming data and uses publicly accessible data streams originating from the Twitter API and the NASDAQ stock market in the tutorials. This book is intended for a one- or two-semester course in data analytics for upper-division undergraduate and graduate students in mathematics, statistics, and computer science. The prerequisites are kept low, and students with one or two courses in probability or statistics, an exposure to vectors and matrices, and a programming course will have no difficulty. The core material of every chapter is accessible to all with these prerequisites. The chapters often expand at the close with innovations of interest to practitioners of data science. Each chapter includes exercises of varying levels of difficulty. The text is eminently suitable for self-study and an exceptional resource for practitioners.