Data Analysis and Decision Making with Microsoft Excel, Revised (with CD-ROM and Decision Tools and Statistic Tools Suite)
Master data analysis, modeling, and spreadsheet use with DATA ANALYSIS AND DECISION MAKING WITH MICROSOFT EXCEL! With a teach-by-example approach, student-friendly writing style, and complete Excel integration, this quantitative methods text provides you with the tools you need to succeed. Margin notes, boxed-in definitions and formulas in the text, enhanced explanations in the text itself, and stated objectives for the examples found throughout the text make studying easy. Problem sets and cases provide realistic examples that enable you to see the relevance of the material to your future as a business leader. The CD-ROMs packaged with every new book include the following add-ins: the Palisade Decision Tools Suite (@RISK, StatTools, PrecisionTree, TopRank, and RISKOptimizer); and SolverTable, which allows you to do sensitivity analysis. All of these add-ins have been revised for Excel 2007.
Anaerobic Digestion: Decision Support Software: Decision Making Tool to evaluate technical, economic and environmental aspects of AD plants development in Ireland
Animal wastes are a significant environmental concern in countries such as Ireland, where meat production activities are an important sector of the national economy. The purpose of this work is to develop a decision support system (DSS) for policy makers to evaluate technical, economic and environmental aspects of anaerobic digestion development in Ireland. The approach involves the production of a livestock and abattoir national database and the development of an algorithmic data- model which allows estimation of the biogas potential production in a given area. This algorithmic approach is supported by a technical, economic and environmental analysis of the technology. Part of the model is a site selection model that helps identify suitable areas for anaerobic digestion plants. The aim is the proposal of a successful method of animal waste management matched with biogas production for means of transport.
This book quickly teaches students the fundamentals of using the SAS system to manage and analyze research data. It is intended for research methods or statistics courses using the SAS System to manage and analyze data in departments of psychology, education, sociology, political science, public administration, statistics, other sciences, and engineering.
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Written by one of the most respected members of the telecommunication community, this book covers the dramatic changes of the past two decades in the field of telecommunications and the rapidly evolving network technologies of the future. Both packet switching, used to improve data communications, and circuit switching, used in telephone networks, are covered in detail from qualitative discussion to performance analysis. A final chapter devoted to combined aspects of both technologies and to future integrated communication networks rounds out the book. This book will prove to be invaluable for telecommunication engineers, managers, network planners, system analysts, designers, programmers, and other technical personnel interested in current and future aspects of telecommunications. 020116423XB04062001
John Chambers turns his attention to R, the enormously successful open-source system based on the S language. His book guides the reader through programming with R, beginning with simple interactive use and progressing by gradual stages, starting with simple functions. More advanced programming techniques can be added as needed, allowing users to grow into software contributors, benefiting their careers and the community. R packages provide a powerful mechanism for contributions to be organized and communicated. This is the only advanced programming book on R, written by the author of the S language from which R evolved.
Mathematical Software: Proceedings of the First International Congress of Mathematical Software Beijing, China 17-19 August 2002
The advent of mathematical software has been one of the most important events in mathematics. Mathematical software systems are used to construct examples, to prove theorems, and to find new mathematical phenomena. On the other hand, mathematical research often motivates developments of new algorithms and new systems. Mathematical software systems rely on the co-operation of mathematicians, designers of algorithms, and mathematical programmers. This volume is aimed at software developers in mathematics and programming mathematicians, but it also provides opportunities to discuss the topics with mathematicians.
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Modeling Dose-response Microarray Data in Early Drug Development Experiments Using R: Order Restricted Analysis of Microarray Data (Use R!)
This book focuses on the analysis of microarray data in the dose-response setting in early drug development experiments in the pharmaceutical industry, the goal being to cover this important topic in early drug development and to provide user-friendly software – R library IsoGene – and a GUI package that can be used to analyze dose-response microarray data. It is intended for biostatisticians in the pharmaceutical industry, biologists who conduct dose-response microarray experiments, and biostatistics/bioinformatics graduate students. All methodological issues in the book are illustrated using four “real-world” examples of early drug development dose-response microarray experiments. In Part I we discuss the dose-response setting and the problem of estimation of normal means under order restrictions. In particular we discuss the pooled-adjacent-violator (PAV) algorithm, isotonic regression, as well as the likelihood ratio test, which will be used in the second part of the book. The core part of the book is Part II. We start with a brief overview of the specific setting of dose-response microarray experiments together with a discussion about the setting, data structure, and the case studies that will be analyzed in later chapters. We demonstrate the use of the IsoGene R library and in particular its graphical capacity. We then focus on the multiplicity problem, which arises when thousands of genes are tested simultaneously. Although multiple testing is discussed in many books and publications related to microarray data analysis, our goal here is to discuss the main concepts and to illustrate how each method can be implemented in practice. In the next step we shift gears and discuss four test statistics that can be used to test for gene significance. We discuss the issue of resampling-based inference and the use of the SAM technique when small-variance genes are present in the data. All the methods discussed in this chapter are implemented in the IsoGene library and the discussion of any methodological issues will be backed up with an illustration of implementation using the IsoGene library. In the following chapters we discuss the issue of identification of the dose-response curve shape, first providing an exploratory tool, an order-restricted bi-clustering technique, which can be used to identify genes with similar dose-response curve shapes before discussing a more formal method to classify the dose-response curves using information criteria. Bayesian models for dose-response microarray data are then discussed, as are model-based approaches, before turning to the concept of multiple contrast tests in the closing chapters.
Spreadsheet Modeling & Decision Analysis: A Practical Introduction to Management Science (with Essential Resources Printed Access Card)
SPREADSHEET MODELING AND DECISION ANALYSIS, Sixth Edition, provides instruction in the most commonly used management science techniques and shows how these tools can be implemented using Microsoft Office Excel 2010.
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Mathematical Frameworks for Component Software: Models for Analysis and Synthesis (Series on Component-Based Software Development)
The range of components technology is both wide and diverse, but some common understanding is emerging through the ideas of model-based development. These include the notions of interfaces, contracts, services, connectors and architectures. Key issues in the application of the technology are becoming clearer, including the consistent integration of different views of a component, component composition, component coordination and transformation for platforms. However, we still know little about theories that support analysis and synthesis of component-based systems. The distinct feature of this volume is its focus on mathematical models that identify the “core” concepts as first class modeling elements, and its providing of techniques for integrating and relating them. The volume contains eleven chapters by well-established researchers writing from different perspectives. Each chapter gives explicit definitions of components in terms of a set of key aspects and addresses some of the problems of integration and analysis of various views: component specification, component composition, component coordination, refinement and substitution, and techniques for solving problems. The concepts and techniques are motivated and explained with the help of examples and case studies.
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An Introduction to Statistics and Data Analysis for Bioinformatics using R (Chapman & Hall/CRC Mathematical & Computational Biology)
From the very basics to linear models, this book provides a complete introduction to statistics, data analysis, and R for bioinformatics research and applications. It covers linear models, ANOVA, cluster analysis, visualization tools, and machine learning techniques. Suitable for self-study and courses in computational biology, bioinformatics, statistics, and the life sciences, the text also presents examples of microarrays and bioinformatics applications. R code illustrates all of the essential concepts and is available on an accompanying CD-ROM.
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