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 ).""

How can you make your bookkeeping workflow smoother and faster? Simple. With this Missing Manual, you're in control: you get step-by-step instructions on how and when to use specific features, along with basic accounting advice to guide you through the learning process. Each page provides insightful tips and tricks to help you become more efficient with QuickBooks 2015. The important stuff you need to know: Get started. Quickly set up your accounts, customers, jobs, and invoice items. Follow the money. Track everything from billable time and expenses to income and profit. Spend less time on bookkeeping. Use QuickBooks to create and reuse bills, invoices, sales receipts, and timesheets. Keep your company financially fit. Examine budgets and actual spending, income, inventory, assets, and liabilities. Find key info fast. Rely on QuickBooks' Search and Find features, as well as the Vendor, Customer, Inventory, and Employee Centers.

Your team is stressed; priorities are unclear. You're not sure what your teammates are working on, and management isn't helping. If your team is struggling with any of these symptoms, these four case studies will guide you to project success. See how Kanban was used to significantly improve time to market and to create a shared focus across marketing, IT, and operations. Each case study comes with illustrations of the Kanban board and diagrams and graphs to help you see behind the scenes. Learn a Lean approach by seeing how Kanban made a difference in four real-world situations. You'll explore how four different teams used Kanban to make paradigm-changing improvements in software development. These teams were struggling with overwork, unclear priorities, and lack of direction. As you discover what worked for them, you'll understand how to make significant changes in real situations.The four case studies in this book explain how to: * Improve the full value chain by using Enterprise Kanban * Boost engagement, teamwork, and flow in change management and operations * Save a derailing project with Kanban * Help an office team outside IT keep up with growth using Kanban What seems easy in theory can become tangled in practice. Discover why "improving IT" can make you miss your biggest improvement opportunities, and why you should focus on fixing quality and front-end operations before IT. Discover how to keep long-term focus and improve across department borders while dealing with everyday challenges. Find out what happened when using Kanban to find better ways to do work in a well-established company, including running multi-team development without a project office. You'll inspire your team and engage management to make it easier to develop better products. What You Need: This is a case study book, so there are no software requirements. The book covers the relevant bits of theory before presenting the case studies.

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."

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 is a new edition of the accessible and student-friendly 'how to' for anyone using R for the first time, for use in spatial statistical analysis, geocomputation and digital mapping. The authors, once again, take readers from 'zero to hero', updating the now standard text to further enable practical R applications in GIS, spatial analyses, spatial statistics, web-scraping and more. Revised and updated, each chapter includes: example data and commands to explore hands-on; scripts and coding to exemplify specific functionality; self-contained exercises for students to work through; embedded code within the descriptive text. The new edition includes detailed discussion of new and emerging packages within R like sf, ggplot, tmap, making it the go to introduction for all researchers collecting and using data with location attached. This is the introduction to the use of R for spatial statistical analysis, geocomputation, and GIS for all researchers - regardless of discipline - collecting and using data with location attached.

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

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. "

This book and app is for practitioners, professionals, researchers, and students who want to learn how to make a plot within the R environment using ggplot2, step-by-step without coding. In widespread use in the statistical communities, R is a free software language and environment for statistical programming and graphics. Many users find R to have a steep learning curve but to be extremely useful once overcome. ggplot2 is an extremely popular package tailored for producing graphics within R but which requires coding and has a steep learning curve itself, and Shiny is an open source R package that provides a web framework for building web applications using R without requiring HTML, CSS, or JavaScript. This manual-"integrating" R, ggplot2, and Shiny-introduces a new Shiny app, Learn ggplot2, that allows users to make plots easily without coding. With the Learn ggplot2 Shiny app, users can make plots using ggplot2 without having to code each step, reducing typos and error messages and allowing users to become familiar with ggplot2 code. The app makes it easy to apply themes, make multiplots (combining several plots into one plot), and download plots as PNG, PDF, or PowerPoint files with editable vector graphics. Users can also make plots on any computer or smart phone. Learn ggplot2 Using Shiny App allows users to Make publication-ready plots in minutes without coding Download plots with desired width, height, and resolution Plot and download plots in png, pdf, and PowerPoint formats, with or without R code and with editable vector graphics

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.

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.

R is now the most widely used statistical package/language in university statistics departments and many research organisations. Its great advantages are that for many years it has been the leading-edge statistical package/language and that it can be freely downloaded from the R web site. Its cooperative development and open code also attracts many contributors meaning that the modelling and data analysis possibilities in R are much richer than in GLIM4, and so the R edition can be substantially more comprehensive than the GLIM4 edition. This text provides a comprehensive treatment of the theory of statistical modelling in R with an emphasis on applications to practical problems and an expanded discussion of statistical theory. A wide range of case studies is provided, using the normal, binomial, Poisson, multinomial, gamma, exponential and Weibull distributions, making this book ideal for graduates and research students in applied statistics and a wide range of quantitative disciplines.

SageMath, or Sage for short, is an open-source mathematical software system based on the Python language and developed by an international community comprising hundreds of teachers and researchers, whose aim is to provide an alternative to the commercial products Magma, Maple, Mathematica, and MATLAB (R). To achieve this, Sage relies on many open-source programs, including GAP, Maxima, PARI, and various scientific libraries for Python, to which thousands of new functions have been added. Sage is freely available and is supported by all modern operating systems. Sage provides a wonderful scientific and graphical calculator for high school students, and it efficiently supports undergraduates in their computations in analysis, linear algebra, calculus, etc. For graduate students, researchers, and engineers in various mathematical specialties, Sage provides the most recent algorithms and tools, which is why several universities around the world already use Sage at the undergraduate level. Computational Mathematics with SageMath, written by researchers and by teachers at the high school, undergraduate, and graduate levels, focuses on the underlying mathematics necessary to use Sage efficiently and is illustrated with concrete examples. Part I is accessible to high school and undergraduate students and Parts II, III, and IV are suitable for graduate students, teachers, and researchers. This book is available under a Creative Commons license at sagebook.gforge.inria.fr.

"This book is a great way to both start learning data science through the promising Julia language and to become an efficient data scientist."- Professor Charles Bouveyron, INRIA Chair in Data Science, Universite Cote d'Azur, Nice, France Julia, an open-source programming language, was created to be as easy to use as languages such as R and Python while also as fast as C and Fortran. An accessible, intuitive, and highly efficient base language with speed that exceeds R and Python, makes Julia a formidable language for data science. Using well known data science methods that will motivate the reader, Data Science with Julia will get readers up to speed on key features of the Julia language and illustrate its facilities for data science and machine learning work. Features: Covers the core components of Julia as well as packages relevant to the input, manipulation and representation of data. Discusses several important topics in data science including supervised and unsupervised learning. Reviews data visualization using the Gadfly package, which was designed to emulate the very popular ggplot2 package in R. Readers will learn how to make many common plots and how to visualize model results. Presents how to optimize Julia code for performance. Will be an ideal source for people who already know R and want to learn how to use Julia (though no previous knowledge of R or any other programming language is required). The advantages of Julia for data science cannot be understated. Besides speed and ease of use, there are already over 1,900 packages available and Julia can interface (either directly or through packages) with libraries written in R, Python, Matlab, C, C++ or Fortran. The book is for senior undergraduates, beginning graduate students, or practicing data scientists who want to learn how to use Julia for data science. "This book is a great way to both start learning data science through the promising Julia language and to become an efficient data scientist." Professor Charles Bouveyron INRIA Chair in Data Science Universite Cote d'Azur, Nice, France

This textbook describes the broadening methodology spectrum of psychological measurement in order to meet the statistical needs of a modern psychologist. The way statistics is used, and maybe even perceived, in psychology has drastically changed over the last few years; computationally as well as methodologically. R has taken the field of psychology by storm, to the point that it can now safely be considered the lingua franca for statistical data analysis in psychology. The goal of this book is to give the reader a starting point when analyzing data using a particular method, including advanced versions, and to hopefully motivate him or her to delve deeper into additional literature on the method. Beginning with one of the oldest psychometric model formulations, the true score model, Mair devotes the early chapters to exploring confirmatory factor analysis, modern test theory, and a sequence of multivariate exploratory method. Subsequent chapters present special techniques useful for modern psychological applications including correlation networks, sophisticated parametric clustering techniques, longitudinal measurements on a single participant, and functional magnetic resonance imaging (fMRI) data. In addition to using real-life data sets to demonstrate each method, the book also reports each method in three parts-- first describing when and why to apply it, then how to compute the method in R, and finally how to present, visualize, and interpret the results. Requiring a basic knowledge of statistical methods and R software, but written in a casual tone, this text is ideal for graduate students in psychology. Relevant courses include methods of scaling, latent variable modeling, psychometrics for graduate students in Psychology, and multivariate methods in the social sciences.

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.

Compositional Data Analysis in Practice is a user-oriented practical guide to the analysis of data with the property of a constant sum, for example percentages adding up to 100%. Compositional data can give misleading results if regular statistical methods are applied, and are best analysed by first transforming them to logarithms of ratios. This book explains how this transformation affects the analysis, results and interpretation of this very special type of data. All aspects of compositional data analysis are considered: visualization, modelling, dimension-reduction, clustering and variable selection, with many examples in the fields of food science, archaeology, sociology and biochemistry, and a final chapter containing a complete case study using fatty acid compositions in ecology. The applicability of these methods extends to other fields such as linguistics, geochemistry, marketing, economics and finance. R Software The following repository contains data files and R scripts from the book https://github.com/michaelgreenacre/CODAinPractice. The R package easyCODA, which accompanies this book, is available on CRAN -- note that you should have version 0.25 or higher. The latest version of the package will always be available on R-Forge and can be installed from R with this instruction: install.packages("easyCODA", repos="http://R-Forge.R-project.org").

Now included with Microsoft Office, Project 2003 is the world's leading project management tool. With extensive help resources and printing assistance, Project 2003 enables users to organize and track tasks and resources efficiently to keep projects on time and within budget.

If you want to realize the immense potential of Microsoft Project 2003 and harness the many features and functionality of this powerful tool, you need "Project 2003 Personal Trainer," It includes everything you want to know about Project 2003--and then plenty more. It's the most complete and engaging tutorial available for Microsoft Project.

As part of O'Reilly's new Personal Trainer Series, this book is based on content from CustomGuide (www.customguide.com), a leading provider of computer training materials that fly in the face of traditional, dry course materials that bore users to tears. CustomGuide is dedicated to delivering courseware, quick references, software bulletins, and e-learning courses that are fun, flexible, and easy to use.

And this book is no exception to their rule. "Project 2003 Personal Trainer" lets you, whatever your technical expertise (or lack thereof), learn exactly what you need to know--at your own pace. Unlike many consumer software tutorials that dumb down (and dull up) the material or make it exceptionally technical and confusing, this book is written in a style that you'll find entertaining, easy to follow, and most of all, clear and informative.

Beginning with the fundamentals of planning and managing a project with Microsoft Project 2003, the book then includes sections on:

working with the task list

managing costs, timelines, and available resources

using the project database

viewing and updating a project

tracking progress

creating reports

handling multiple projects

The fully illustrated "Project 2003 Personal Trainer" features dozens of time-saving, task-oriented lessons, includes detailed diagrams, and comes with a fully interactive CD tutorial to guide your learning--everything you need to become a Project pro.

This book discusses all major topics on survey sampling and estimation. It covers traditional as well as advanced sampling methods related to the spatial populations. The book presents real-world applications of major sampling methods and illustrates them with the R software. As a large sample size is not cost-efficient, this book introduces a new method by using the domain knowledge of the negative correlation between the variable of interest and the auxiliary variable in order to control the size of a sample. In addition, the book focuses on adaptive cluster sampling, rank-set sampling and their applications in real life. Advance methods discussed in the book have tremendous applications in ecology, environmental science, health science, forestry, bio-sciences, and humanities. This book is targeted as a text for undergraduate and graduate students of statistics, as well as researchers in various disciplines.

Sufficient dimension reduction is a rapidly developing research field that has wide applications in regression diagnostics, data visualization, machine learning, genomics, image processing, pattern recognition, and medicine, because they are fields that produce large datasets with a large number of variables. Sufficient Dimension Reduction: Methods and Applications with R introduces the basic theories and the main methodologies, provides practical and easy-to-use algorithms and computer codes to implement these methodologies, and surveys the recent advances at the frontiers of this field. Features Provides comprehensive coverage of this emerging research field. Synthesizes a wide variety of dimension reduction methods under a few unifying principles such as projection in Hilbert spaces, kernel mapping, and von Mises expansion. Reflects most recent advances such as nonlinear sufficient dimension reduction, dimension folding for tensorial data, as well as sufficient dimension reduction for functional data. Includes a set of computer codes written in R that are easily implemented by the readers. Uses real data sets available online to illustrate the usage and power of the described methods. Sufficient dimension reduction has undergone momentous development in recent years, partly due to the increased demands for techniques to process high-dimensional data, a hallmark of our age of Big Data. This book will serve as the perfect entry into the field for the beginning researchers or a handy reference for the advanced ones. The author Bing Li obtained his Ph.D. from the University of Chicago. He is currently a Professor of Statistics at the Pennsylvania State University. His research interests cover sufficient dimension reduction, statistical graphical models, functional data analysis, machine learning, estimating equations and quasilikelihood, and robust statistics. He is a fellow of the Institute of Mathematical Statistics and the American Statistical Association. He is an Associate Editor for The Annals of Statistics and the Journal of the American Statistical Association.

Explore the inner workings of environmental processes using a mathematical approach. Environmental Systems Analysis with MATLAB (R) combines environmental science concepts and system theory with numerical techniques to provide a better understanding of how our environment works. The book focuses on building mathematical models of environmental systems, and using these models to analyze their behaviors. Designed with the environmental professional in mind, it offers a practical introduction to developing the skills required for managing environmental modeling and data handling. The book follows a logical sequence from the basic steps of model building and data analysis to implementing these concepts into working computer codes, and then on to assessing their results. It describes data processing (rarely considered in environmental analysis); outlines the tools needed to successfully analyze data and develop models, and moves on to real-world problems. The author illustrates in the first four chapters the methodological aspects of environmental systems analysis, and in subsequent chapters applies them to specific environmental concerns. The accompanying software bundle is freely downloadable from the book web site. It follows the chapters sequence and provides a hands-on experience, allowing the reader to reproduce the figures in the text and experiment by varying the problem setting. A basic MATLAB literacy is required to get the most out of the software. Ideal for coursework and self-study, this offering: Deals with the basic concepts of environmental modeling and identification, both from the mechanistic and the data-driven viewpoint Provides a unifying methodological approach to deal with specific aspects of environmental modeling: population dynamics, flow systems, and environmental microbiology Assesses the similarities and the differences of microbial processes in natural and man-made environments Analyzes several aquatic ecosystems' case studies Presents an application of an extended Streeter & Phelps (S&P) model Describes an ecological method to estimate the bioavailable nutrients in natural waters Considers a lagoon ecosystem from several viewpoints, including modeling and management, and more

Der enorme Kostendruck in Industrieunternehmen sowie der erkennbare Wandel der Wertschopfungsketten hin zu Wertschopfungsnetzwerken werden die Bedeutung der Beschaffung auf den Unternehmenserfolg sowie die Komplexitat der Beschaffungsaufgaben noch weiter erhohen. Diese Herausforderung kann nur durch den verstarkten Einsatz geeigneter, prozessorientierter Informationstechnologie bei der Beschaffung direkter Guter bewaltigt werden.

Dieses Buch bietet durch die Darstellung des State-of-the-Art und der Entwicklungstendenzen aus Sicht der Wissenschaft sowie namhafter IT-Anbieter-, Beratungs- und Industrieunternehmen erstmals einen ganzheitlichen Uberblick uber Strategien, Prozesse und Systeme bei der Beschaffung direkter Guter. Daraus konnen Handlungsempfehlungen fur die konkrete Ausgestaltung in den Unternehmen gewonnen werden."

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.