Your bookkeeping workflow will be smoother and faster with QuickBooks 2012 - but only if you spend more time using the program than figuring out how it works. Take control with this Missing Manual. You'll not only learn how and when to use specific features, you'll also get basic accounting advice to help you through the learning process. * Set up QuickBooks. Arrange files and preferences to suit your company's needs. * Manage your business. Track inventory, control spending, run payroll, and handle income. * Follow the money. Examine everything from customer invoices to year-end tasks. * Find key info quickly. Take advantage of QuickBooks' reports, Company Snapshot, and search tools. * Streamline your workflow. Set up the Home page and Online Banking Center to meet your requirements. * Build and monitor budgets. Learn how to keep your company financially fit. * Share your financial data. Work with your accountant more efficiently.

To date, statistics has tended to be neatly divided into two theoretical approaches or frameworks: frequentist (or classical) and Bayesian. Scientists typically choose the statistical framework to analyse their data depending on the nature and complexity of the problem, and based on their personal views and prior training on probability and uncertainty. Although textbooks and courses should reflect and anticipate this dual reality, they rarely do so. This accessible textbook explains, discusses, and applies both the frequentist and Bayesian theoretical frameworks to fit the different types of statistical models that allow an analysis of the types of data most commonly gathered by life scientists. It presents the material in an informal, approachable, and progressive manner suitable for readers with only a basic knowledge of calculus and statistics. Statistical Modeling with R is aimed at senior undergraduate and graduate students, professional researchers, and practitioners throughout the life sciences, seeking to strengthen their understanding of quantitative methods and to apply them successfully to real world scenarios, whether in the fields of ecology, evolution, environmental studies, or computational biology.

In biological research, the amount of data available to researchers has increased so much over recent years, it is becoming increasingly difficult to understand the current state of the art without some experience and understanding of data analytics and bioinformatics. An Introduction to Bioinformatics with R: A Practical Guide for Biologists leads the reader through the basics of computational analysis of data encountered in modern biological research. With no previous experience with statistics or programming required, readers will develop the ability to plan suitable analyses of biological datasets, and to use the R programming environment to perform these analyses. This is achieved through a series of case studies using R to answer research questions using molecular biology datasets. Broadly applicable statistical methods are explained, including linear and rank-based correlation, distance metrics and hierarchical clustering, hypothesis testing using linear regression, proportional hazards regression for survival data, and principal component analysis. These methods are then applied as appropriate throughout the case studies, illustrating how they can be used to answer research questions. Key Features: * Provides a practical course in computational data analysis suitable for students or researchers with no previous exposure to computer programming. * Describes in detail the theoretical basis for statistical analysis techniques used throughout the textbook, from basic principles * Presents walk-throughs of data analysis tasks using R and example datasets. All R commands are presented and explained in order to enable the reader to carry out these tasks themselves. * Uses outputs from a large range of molecular biology platforms including DNA methylation and genotyping microarrays; RNA-seq, genome sequencing, ChIP-seq and bisulphite sequencing; and high-throughput phenotypic screens. * Gives worked-out examples geared towards problems encountered in cancer research, which can also be applied across many areas of molecular biology and medical research. This book has been developed over years of training biological scientists and clinicians to analyse the large datasets available in their cancer research projects. It is appropriate for use as a textbook or as a practical book for biological scientists looking to gain bioinformatics skills.

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

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.

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.

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.

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 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.

Develop a complete authorization concept for SAP S/4HANA and SAP Fiori with this guide! Start by understanding how authorizations work in an ABAP system and exploring the main transactions you'll use for configuration. Then learn to create roles with Transaction SU24 and the Profile Generator, track and correct missing authorizations with traces, manage users, and more. See how SAP Access Control can be a useful tool to manage authorizations and learn to migrate authorizations to SAP S/4HANA. Highlights include:1) ABAP authorizations2) Roles3) Transaction SU24 4) Profile Generator5) Authorization traces6) User maintenance7) SAP Access Control8) Debugging9) Migration10) Xiting Authorizations Management Suite (XAMS)

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

From A to Z, or more appropriately, from AB01 to XK99, this is the SAP transaction code encyclopedia you've been waiting for! Learn how to use more than 3,000 transaction codes with ease in your daily SAP ERP work, whether your focus is in Financials, Logistics, HR, or all of the above. With T-codes categorized by application, title, and task, this guide will teach you how to circumvent the menu tree and shortcut your way through SAP. a. All Major Modules: Find all the critical transactions for Financials and Controlling, Inventory Management, Materials Management, Warehouse Management, Production Planning, Sales and Distribution, Plant Maintenance, Quality Management, Project System, HCM, and the Basis system. b. Transaction Functions and Descriptions: Get comprehensive descriptions of each transaction's function and input, and understand how it compares to related transactions. c. Easy Access: Delve into an individual SAP ERP module, where transactions are listed alphabetically, or search for codes using the index. Highlights: Financials and Controlling Materials Management Warehouse Management Inventory Management Production Planning Sales and Distribution Plant Maintenance Quality Management Project System Human Capital Management Basis system

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.

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

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.

You think agile techniques might be for you, but your projects and organization are unique. An "out-of-the-box" agile approach won't work. Instead, unite agile and lean principles for your project. See how to design a custom approach, reap the benefits of collaboration, and deliver value. For project managers who want to use agile techniques, managers who want to start, and technical leaders who want to know more and succeed, this book is your first step toward agile project success. You've tried to use an off-the-shelf approach to agile techniques, and it's not working. Instead of a standard method or framework, work from agile and lean principles to design your own agile approach in a way that works for you. Build collaborative, cross-functional teams. See how small batch sizes and frequent delivery create an environment of trust and transparency between the team, management, and customers. Learn about the interpersonal skills that help agile teams work together so well. In addition to seeing work and knowing what "done" means, you'll see examples of many possible team-based measurements. Look at tools you can use for status reporting, and how to use those measurements to help your managers understand what agile techniques buy them. Recognize the traps that prevent agile principles from working in too many organizations, and what to do about those traps. Use agile techniques for workgroups, and see what managers can do to create and nurture an agile culture. You might be surprised at how few meetings and rituals you need to still work in an agile way. Johanna's signature frankness and humor will get you on the right track to design your agile project to succeed. What You Need: No technical expertise or experience needed, just a desire to know more about how you might use agile in your project.

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").

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.