R for College Mathematics and Statistics encourages the use of R in mathematics and statistics courses. Instructors are no longer limited to ``nice'' functions in calculus classes. They can require reports and homework with graphs. They can do simulations and experiments. R can be useful for student projects, for creating graphics for teaching, as well as for scholarly work. This book presents ways R, which is freely available, can enhance the teaching of mathematics and statistics. R has the potential to help students learn mathematics due to the need for precision, understanding of symbols and functions, and the logical nature of code. Moreover, the text provides students the opportunity for experimenting with concepts in any mathematics course. Features: Does not require previous experience with R Promotes the use of R in typical mathematics and statistics course work Organized by mathematics topics Utilizes an example-based approach Chapters are largely independent of each other

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

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

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

Business Process Change: A Business Process Management Guide for Managers and Process Professionals, Fourth Edition, provides a balanced view of the field of business process change. Bestselling author and renowned expert in the field Paul Harmon offers concepts, methods, cases for all aspects, and phases of successful business process improvement. Students and professionals alike will benefit from the comprehensive coverage and customizable, integrated approach to broad business process management that focuses on improving efficiency and productivity. In this updated Edition, particular attention is paid to the impact of disruptive technology on business and the need for agile transformation.

Quicken is one of the many convenient ways to keep track of personal finances, but many people are unaware of Quicken's power and end up using only the basic features. And sometimes Quicken seems to raise more questions than it answers: Return of capital from stock? "Net worth"? What are they and why do you need to know about them? Luckily, "Quicken 2008: The Missing Manual" picks up where Quicken's help resources leave off. You'll find step-by-step instructions for using the most useful Quicken features, including those you may not have quite understood, let alone mastered, such as budgeting, recording investment transactions, archiving Quicken data files, and so on. You also learn why and when to use specific features, and which ones would be most useful in your situation." Quicken 2008: The Missing Manual" helps you: set up Quicken to take care of your specific needs; follow your money from the moment you earn it; make deposits, pay for expenses, track the things you own and how much you owe; take care of financial tasks online, and quickly reconcile your accounts; create and use budgets and track your investments; generate reports to prepare your tax returns and evaluate your financial fitness; and a lot more. This book is designed to accommodate readers at every technical level. If you're a first-time Quicken user, special boxes with the title "Up To Speed" provide the introductory information you need to understand the topic at hand. For advanced users, there are similar boxes called "Power Users' Clinic" that offer more technical tips, tricks, and shortcuts for the experienced Quicken fan. For a topic as important as your personal finances, why trust anything else?

The application and interpretation of statistics are central to ecological study and practice. Ecologists are now asking more sophisticated questions than in the past. These new questions, together with the continued growth of computing power and the availability of new software, have created a new generation of statistical techniques. These have resulted in major recent developments in both our understanding and practice of ecological statistics. This novel book synthesizes a number of these changes, addressing key approaches and issues that tend to be overlooked in other books such as missing/censored data, correlation structure of data, heterogeneous data, and complex causal relationships. These issues characterize a large proportion of ecological data, but most ecologists' training in traditional statistics simply does not provide them with adequate preparation to handle the associated challenges. Uniquely, Ecological Statistics highlights the underlying links among many statistical approaches that attempt to tackle these issues. In particular, it gives readers an introduction to approaches to inference, likelihoods, generalized linear (mixed) models, spatially or phylogenetically-structured data, and data synthesis, with a strong emphasis on conceptual understanding and subsequent application to data analysis. Written by a team of practicing ecologists, mathematical explanations have been kept to the minimum necessary. This user-friendly textbook will be suitable for graduate students, researchers, and practitioners in the fields of ecology, evolution, environmental studies, and computational biology who are interested in updating their statistical tool kits. A companion web site provides example data sets and commented code in the R language.

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

Unique reference book covering the entire field of accounting information systems. Contributions from an international range of accounting and information systems experts. Includes coverage of contemporary themes such as big data, data security, cloud computing, IoT and blockchain.

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

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

An Up-to-Date, All-in-One Resource for Using SAS and R to Perform Frequent TasksThe first edition of this popular guide provided a path between SAS and R using an easy-to-understand, dictionary-like approach. Retaining the same accessible format, SAS and R: Data Management, Statistical Analysis, and Graphics, Second Edition explains how to easily perform an analytical task in both SAS and R, without having to navigate through the extensive, idiosyncratic, and sometimes unwieldy software documentation. The book covers many common tasks, such as data management, descriptive summaries, inferential procedures, regression analysis, and graphics, along with more complex applications. New to the Second EditionThis edition now covers RStudio, a powerful and easy-to-use interface for R. It incorporates a number of additional topics, including using application program interfaces (APIs), accessing data through database management systems, using reproducible analysis tools, and statistical analysis with Markov chain Monte Carlo (MCMC) methods and finite mixture models. It also includes extended examples of simulations and many new examples. Enables Easy Mobility between the Two SystemsThrough the extensive indexing and cross-referencing, users can directly find and implement the material they need. SAS users can look up tasks in the SAS index and then find the associated R code while R users can benefit from the R index in a similar manner. Numerous example analyses demonstrate the code in action and facilitate further exploration. The datasets and code are available for download on the book's website.

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

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

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

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

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

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

Das Buch gibt eine Einfuhrung in die Geschaftsprozessanalyse mit den beiden Schwerpunkten "Ereignisgesteuerte Prozessketten" (EPK) und "objektorientierte Geschaftsprozessanalyse." Es thematisiert Grundlagen, Chancen und Risiken Betriebswirtschaftlicher Standardsoftware (ERP-Software) und gibt eine umfassende Einfuhrung in ereignisgesteuerte Prozessketten. Die Darstellung wird durch zahlreiche Beispiele aus der Praxis abgerundet. Anschliessend wird das Gesamtkonzept der Unternehmensmodellierung fur SAP R/3 beschrieben und aufgezeigt, welche zentrale Rolle ereignisgesteuerte Prozessketten dabei spielen. Das Buch stellt Objektorientierung vor und uberpruft die objektorientierte Geschaftsprozessmodellierung auf ihre Tauglichkeit fur eine effiziente Prozessanalyse. In der Neuauflage wurde der Schwerpunkt auf die Modellierungsmethoden verlagert. Das Kapitel zur objektorientierten Geschaftsprozessmodellierung wurde stark ausgebaut und aktualisiert (UML 2.0) und das EPK-Kapitel um weitere Beispiele erweitert."

There have been many improvements to QuickBooks over the years, but the program's documentation is not one of them. Luckily, QuickBooks 2008: The Missing Manual picks up where QuickBook's help resources leave off. With this book, you don't just learn how to use the software, you learn why and when to use specific features. And you get basic accounting advice so that it all makes sense to you along the way. With its Simple Start, Basic, Pro, Premier, and industry-specific Enterprise editions, QuickBooks can handle many of the financial tasks companies face, but the price you pay is an overabundance of features. With this book, you get advice on which features you need to use to get your work done efficiently, along with step-by-step instructions on how to use them. QuickBooks 2008: The Missing Manual helps you: *Get more out of QuickBooks whether you're a beginner or an old pro. *Learn how QuickBooks can help you boost sales, control spending, and save on taxes. *Set up and manage your files to fit your company's specific needs. *Use QuickBooks reports to evaluate every aspect of your enterprise. *Follow the money all the way from customer invoices to year-end tasks. *Discover new tips and tricks on the best timesaving options for your business. *Build budgets and plan for the future to make your business more successful. And a lot more. This book is designed to accommodate readers at every technical level. If you're a first-time QuickBooks user, special boxes with the title "Up To Speed" provide the introductory information you need to understand the topic at hand. For advanced users, there are similar boxes called "Power Users' Clinic" that offer more technical tips, tricks, and shortcuts for the experienced QuickBooks fan. For a topic as complicated as accounting software, why trust anything else?

An R Companion to Applied Regression is a broad introduction to the R statistical computing environment in the context of applied regression analysis. John Fox and Sanford Weisberg provide a step-by-step guide to using the free statistical software R, an emphasis on integrating statistical computing in R with the practice of data analysis, coverage of generalized linear models, and substantial web-based support materials. The Third Edition has been reorganized and includes a new chapter on mixed-effects models, new and updated data sets, and a de-emphasis on statistical programming, while retaining a general introduction to basic R programming. The authors have substantially updated both the car and effects packages for R for this edition, introducing additional capabilities and making the software more consistent and easier to use. They also advocate an everyday data-analysis workflow that encourages reproducible research. To this end, they provide coverage of RStudio, an interactive development environment for R that allows readers to organize and document their work in a simple and intuitive fashion, and then easily share their results with others. Also included is coverage of R Markdown, showing how to create documents that mix R commands with explanatory text. "An R Companion to Applied Regression continues to provide the most comprehensive and user-friendly guide to estimating, interpreting, and presenting results from regression models in R." -Christopher Hare, University of California, Davis

Statistics is of ever-increasing importance in Science and Technology and this book presents the essentials of the subject in a form suitable either as the basis of a course of lectures or to be read and/or used on its own. It assumes very little in the way of mathematical knowledge-just the ability to substitute numerically in a few simple formulae. However, some mathematical proofs are outlined or given in full to illustrate the derivation of the subject; these can be omitted without loss of understanding. The book does aim at making clear the scope and nature of those essential tests and methods that a scientist or technologist is likely to need; to this end each chapter has been divided into sections with their own subheadings and some effort has been made to make the text unambiguous (if any reader finds a misleading point anywhere I hope he will write to me about it). Also with this aim in view, the equality of probability to proportion of population is stated early, then the normal distribution and the taking of samples is discussed. This occupies the first five chapters. With the principles of these chapters understood, the student can immediately learn the significance tests of Chapter 6 and, if he needs it, the analysis of variance of Chapter 7. For some scientists this will be most of what they need. Howcver, they will be in a position to read and/or use the remaining chapters without undue difficulty.

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.

Upgrade your knowledge to learn S/4HANA, the latest version of the SAP ERP system, with its built-in intelligent technologies, including AI, machine learning, and advanced analytics.Since the first edition of this book published as SAP ERP Financial and Controlling: Configuration and Use Management, the perspective has changed significantly as S/4HANA now comes with new features, such as FIORI (new GUI), which focuses on flexible app style development and interactivity with mobile phones. It also has a universal journal, which helps in data integration in a single location, such as centralized processing, and is faster than ECC S/3. It merges FI & CO efficiently, which enables document posting in the Controlling area setup. General Ledger Accounts (FI) and Cost Element (CO) are mapped together in a way that cost elements (both primary and secondary) are part of G/L accounts. And a mandatory setup of customer-vendor integration with business partners is included vs the earlier ECC creation with separate vendor master and customer master. This updated edition presents new features in SAP S/4HANA, with in-depth coverage of the FI syllabus in SAP S/4HANA. A practical and hands-on approach includes scenarios with real-life examples and practical illustrations. There is no unnecessary jargon in this configuration and end-user manual. What You Will Learn Configure SAP FI as a pro in S/4 Master core aspects of Financial Accounting and Controlling Integrate SAP Financial with other SAP modules Gain a thorough hands-on experience with IMG (Implementation Guide) Understand and explain the functionalities of SAP FI Who This Book Is For FI consultants, trainers, developers, accountants, and SAP FI support organizations will find the book an excellent reference guide. Beginners without prior FI configuration experience will find the step-by-step illustrations to be practical and great hands-on experience.

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.

Employ essential tools and functions of the MATLAB and Simulink packages, which are explained and demonstrated via interactive examples and case studies. This revised edition covers features from the latest MATLAB 2022b release, as well as other features that have been released since the first edition published. This book contains dozens of simulation models and solved problems via m-files/scripts and Simulink models which will help you to learn programming and modelling essentials. You'll become efficient with many of the built-in tools and functions of MATLAB/Simulink while solving engineering and scientific computing problems. Beginning MATLAB and Simulink, Second Edition explains various practical issues of programming and modelling in parallel by comparing MATLAB and Simulink. After studying and using this book, you'll be proficient at using MATLAB and Simulink and applying the source code and models from the book's examples as templates for your own projects in data science or engineering. What You Will Learn Master the programming and modelling essentials of MATLAB and Simulink Carry out data visualization with MATLAB Build a GUI and develop App with MATLAB Work with integration and numerical root finding methods Apply MATLAB to differential equations-based models and simulations Use MATLAB and Simulink for data science projects Who This Book Is ForEngineers, programmers, data scientists, and students majoring in engineering and scientific computing who are new to MATLAB and Simulink.

Manufacturing Execution Systeme (MES) sind das Werkzeug, mit dem die Fertigungsprozesse transparent gemacht werden und mit dem die Ablaufe in Realtime unter Berucksichtigung von Zielvorgaben geregelt werden konnen.

Das Buch soll helfen, ein MES zielorientiert im Unternehmen einzufuhren. Hierzu werden nicht nur Ratschlage zur Konzeption gegeben, sondern es wird auch bei der "internen Vermarktung" des MES-Vorhabens in Form von Ratschlagen und Wirtschaftlichkeitsbetrachtungen unterstutzt. Im Anschluss daran werden Hinweise zur Erstellung eines Pflichtenhefts sowie zur Ausschreibung und Anbieterauswahl gegeben. Neben Tipps vom Projektstart bis zum Produktivstart des Systems werden Themen wie Mitarbeiterqualifizierung und Support angesprochen. Ferner wird aufgezeigt, wie der Einfuhrungsprozess durch externe MES-Berater unterstutzt werden kann.

Zwei Fallbeispiele zeigen, wie die Einfuhrung in der Praxis verlief und welcher Nutzen durch das MES erzielt werden konnte.

Zur Besserung Nutzung des Systems werden noch organisatorische Massnahmen beschrieben, wie die Mitarbeitereinbindung mit Zielvereinbarungen und Pramienentlohnung, die auch neue Tarifmodelle, wie z.B. ERA (Entgeltrahmenabkommen) vorsehen.

Ein Kapitel mit Checklisten, Literaturtipps und Weblinks schliesst dieses Buch ab."

Take control of your personal finances with this popular, easy guide

Quicken is the country's most popular and highly recommended personal finance software, and with "Quicken For Dummies," you can harness the power of this practical financial tool to manage bills, reconcile bank accounts, track investments, and much more

Personal finance expert and CPA Stephen L. Nelson lends his expertise to this accessible, easy-to-read guide, which has been fully updated to reflect the new features of Quicken available in its newest version. You can quickly learn how to use Quicken to record credit card transactions, track mortgages and other liabilities, minimize taxes, maximize savings, maintain detailed records, and build a solid foundation for creating better financial plans.Covers updated features in the newest version of the increasingly popular Quicken softwareEmpowers readers to fight the bad habits and decisions that lead to large debts and minimal or nonexistent savingsDemystifies the software's features for tracking everyday finances, managing investments, and evaluating the tax implications of financial decisionsOffers invaluable advice and expertise from author Stephen L. Nelson, a recognized authority on personal finance

Every step toward better finances is a step in the right direction. Let "Quicken For Dummies" start your journey toward increased savings, lowered debt, and a more secure financial future.

Das Buch behandelt praxisbezogene Methoden zur Analyse und Steuerung operationaler IT-Risiken entsprechend der Anforderungen im Gesetz zur Kontrolle und Transparenz im Unternehmensbereich (KonTraG). Prasentiert werden zudem Konzepte fur den Aufbau und den Ablauf einer Notfall- und Krisenorganisation in Unternehmen sowie Verfahren zur Pravention und Durchfuhrung von Ubungen im Not- oder Katastrophenfall. Zu den Praxisbeispielen werden Checklisten zur Verfugung gestellt, die als Referenz bei der Erstellung eigener Dokumente dienen."