Praise for the First Edition ". . . an excellent textbook . . . well organized and neatly written." — Mathematical Reviews ". . . amazingly interesting . . ." — Technometrics Thoroughly updated to showcase the interrelationships between probability, statistics, and stochastic processes, Probability, Statistics, and Stochastic Processes, Second Edition prepares readers to collect, analyze, and characterize data in their chosen fields. Beginning with three chapters that develop probability theory and introduce the axioms of probability, random variables, and joint distributions, the book goes on to present limit theorems and simulation. The authors combine a rigorous, calculus-based development of theory with an intuitive approach that appeals to readers' sense of reason and logic. Including more than 400 examples that help illustrate concepts and theory, the Second Edition features new material on statistical inference and a wealth of newly added topics, including: Consistency of point estimators Large sample theory Bootstrap simulation Multiple hypothesis testing Fisher's exact test and Kolmogorov-Smirnov test Martingales, renewal processes, and Brownian motion One-way analysis of variance and the general linear model Extensively class-tested to ensure an accessible presentation, Probability, Statistics, and Stochastic Processes, Second Edition is an excellent book for courses on probability and statistics at the upper-undergraduate level. The book is also an ideal resource for scientists and engineers in the fields of statistics, mathematics, industrial management, and engineering.

This volume provides an overview of the methodological issues and challenges inherent in the study of small groups from the perspective of seasoned researchers in communication, psychology and other fields in the behavioral and social sciences. It summarizes the current state of group methods in a format that is readable, insightful, and useful for both new and experienced group researchers. This collection of essays will inspire new and established researchers alike to look beyond their current methodological approaches, covering both traditional and new methods for studying groups and exploring the full range of groups in face-to-face and online settings. The volume will be an important addition to graduate study on group research and will be a valuable reference for established group researchers, consultants and other practitioners. The essays in this volume when considered as a whole will be a contemporary interdisciplinary integration on group research methods.

Most designers know that yellow text presented against a blue background reads clearly and easily, but how many can explain why, and what really are the best ways to help others and ourselves clearly see key patterns in a bunch of data? When we use software, access a website, or view business or scientific graphics, our understanding is greatly enhanced or impeded by the way the information is presented. This book explores the art and science of why we see objects the way we do. Based on the science of perception and vision, the author presents the key principles at work for a wide range of applications--resulting in visualization of improved clarity, utility, and persuasiveness. The book offers practical guidelines that can be applied by anyone: interaction designers, graphic designers of all kinds (including web designers), data miners, and financial analysts. Complete update of the recognized source in industry, research, and academic for applicable guidance on information visualizing Includes the latest research and state of the art information on multimedia presentation More than 160 explicit design guidelines based on vision science A new final chapter that explains the process of visual thinking and how visualizations help us to think about problems Packed with over 400 informative full color illustrations, which are key to understanding of the subject

Understanding the basic concepts of character encoding is necessary for creating, manipulating, and rendering any type of character data. An encoding is involved whenever data is brought into SAS from various external sources; whenever data is transferred between SAS applications running different locales or across the network via thin clients; and when output is written to external files, SAS data sets, printers, or Web pages. In each of these cases, something can go wrong. It is the encoder’s responsibility to ensure that the data is stored, processed, and rendered in the correct encoding. Manfred Kiefer's SAS Encoding: Understanding the Details explains the basic concepts of characters, encodings, glyphs, and fonts and gives practical examples of how to troubleshoot encoding problems. Addressed to the beginner as well as to the advanced SAS user, this book can help solve your encoding problems. It provides background information about encodings, shows how they are used with SAS software, and explains typical problems and ways to sort those out. It also presents examples of how to set up SAS software in an international environment.

Generally, books on mathematical statistics are restricted to the case of independent identically distributed random variables. In this book however, both this case AND the case of dependent variables, i.e. statistics for discrete and continuous time processes, are studied. This second case is very important for today's practitioners. Mathematical Statistics and Stochastic Processes is based on decision theory and asymptotic statistics and contains up-to-date information on the relevant topics of theory of probability, estimation, confidence intervals, non-parametric statistics and robustness, second-order processes in discrete and continuous time and diffusion processes, statistics for discrete and continuous time processes, statistical prediction, and complements in probability. This book is aimed at students studying courses on probability with an emphasis on measure theory and for all practitioners who apply and use statistics and probability on a daily basis.

This book presents statistical models that have recently been developed within several research communities to access information contained in text collections. The problems considered are linked to applications aiming at facilitating information access: - information extraction and retrieval; - text classification and clustering; - opinion mining; - comprehension aids (automatic summarization, machine translation, visualization). In order to give the reader as complete a description as possible, the focus is placed on the probability models used in the applications concerned, by highlighting the relationship between models and applications and by illustrating the behavior of each model on real collections. Textual Information Access is organized around four themes: informational retrieval and ranking models, classification and clustering (regression logistics, kernel methods, Markov fields, etc.), multilingualism and machine translation, and emerging applications such as information exploration. Contents Part 1: Information Retrieval 1. Probabilistic Models for Information Retrieval, Stéphane Clinchant and Eric Gaussier. 2. Learnable Ranking Models for Automatic Text Summarization and Information Retrieval, Massih-Réza Amini, David Buffoni, Patrick Gallinari, Tuong Vinh Truong and Nicolas Usunier. Part 2: Classification and Clustering 3. Logistic Regression and Text Classification, Sujeevan Aseervatham, Eric Gaussier, Anestis Antoniadis, Michel Burlet and Yves Denneulin. 4. Kernel Methods for Textual Information Access, Jean-Michel Renders. 5. Topic-Based Generative Models for Text Information Access, Jean-Cédric Chappelier. 6. Conditional Random Fields for Information Extraction, Isabelle Tellier and Marc Tommasi. Part 3: Multilingualism 7. Statistical Methods for Machine Translation, Alexandre Allauzen and François Yvon. Part 4: Emerging Applications 8. Information Mining: Methods and Interfaces for Accessing Complex Information, Josiane Mothe, Kurt Englmeier and Fionn Murtagh. 9. Opinion Detection as a Topic Classification Problem, Juan-Manuel Torres-Moreno, Marc El-Bèze, Patrice Bellot and Fréderic Béchet.

How-to guidance for measuring lost profits due to business interruption damages A Quantitative Approach to Commercial Damages explains the complicated process of measuring business interruption damages, whether they are losses are from natural or man-made disasters, or whether the performance of one company adversely affects the performance of another. Using a methodology built around case studies integrated with solution tools, this book is presented step by step from the analysis damages perspective to aid in preparing a damage claim. Over 250 screen shots are included and key cell formulas that show how to construct a formula and lay it out on the spreadsheet. Includes Excel spreadsheet applications and key cell formulas for those who wish to construct their own spreadsheets Offers a step-by-step approach to computing damages using case studies and over 250 screen shots Often in the course of business, a firm will be damaged by the actions of another individual or company, such as a fire that shuts down a restaurant for two months. Often, this results in the filing of a business interruption claim. Discover how to measure business losses with the proven guidance found in A Quantitative Approach to Commercial Damages.

This book is the definitive guide to cash flow statement analysis and forecasting. It takes the reader from an introduction about how cash flows move within a business, through to a detailed review of the contents of a cash flow statement. This is followed by detailed guidance on how to restate cash flows into a template format. The book shows how to use the template to analyse the data from start up, growth, mature and declining companies, and those using US GAAP and IAS reporting. The book includes real world examples from such companies as Black and Decker (US), Fiat (Italy) and Tesco (UK). A section on cash flow forecasting includes full coverage of spreadsheet risk and good practice. Complete with chapters of particular interest to those involved in credit markets as lenders or counter-parties, those running businesses and those in equity investing, this book is the definitive guide to understanding and interpreting cash flow data.

Bayesian analysis of complex models based on stochastic processes has in recent years become a growing area. This book provides a unified treatment of Bayesian analysis of models based on stochastic processes, covering the main classes of stochastic processing including modeling, computational, inference, forecasting, decision making and important applied models. Key features: Explores Bayesian analysis of models based on stochastic processes, providing a unified treatment. Provides a thorough introduction for research students. Computational tools to deal with complex problems are illustrated along with real life case studies Looks at inference, prediction and decision making. Researchers, graduate and advanced undergraduate students interested in stochastic processes in fields such as statistics, operations research (OR), engineering, finance, economics, computer science and Bayesian analysis will benefit from reading this book. With numerous applications included, practitioners of OR, stochastic modelling and applied statistics will also find this book useful.

Reveals how to build rich BI reports with just a few clicks using Crescent, Microsoft’s newest BI tool Technical review by Microsoft’s Crescent team and Foreword by Group Program Manager for Crescent Complete, practical examples are immediately usable to readers in a commercial environment CD-ROM contains 30+ reusable reports, all code samples, and supporting animations that walk thru each example

Modelling has permeated virtually all areas of industrial, environmental, economic, bio-medical or civil engineering: yet the use of models for decision-making raises a number of issues to which this book is dedicated: How uncertain is my model ? Is it truly valuable to support decision-making ? What kind of decision can be truly supported and how can I handle residual uncertainty ? How much refined should the mathematical description be, given the true data limitations ? Could the uncertainty be reduced through more data, increased modeling investment or computational budget ? Should it be reduced now or later ? How robust is the analysis or the computational methods involved ? Should / could those methods be more robust ? Does it make sense to handle uncertainty, risk, lack of knowledge, variability or errors altogether ? How reasonable is the choice of probabilistic modeling for rare events ? How rare are the events to be considered ? How far does it make sense to handle extreme events and elaborate confidence figures ? Can I take advantage of expert / phenomenological knowledge to tighten the probabilistic figures ? Are there connex domains that could provide models or inspiration for my problem ? Written by a leader at the crossroads of industry, academia and engineering, and based on decades of multi-disciplinary field experience, Modelling Under Risk and Uncertainty gives a self-consistent introduction to the methods involved by any type of modeling development acknowledging the inevitable uncertainty and associated risks. It goes beyond the "black-box" view that some analysts, modelers, risk experts or statisticians develop on the underlying phenomenology of the environmental or industrial processes, without valuing enough their physical properties and inner modelling potential nor challenging the practical plausibility of mathematical hypotheses; conversely it is also to attract environmental or engineering modellers to better handle model confidence issues through finer statistical and risk analysis material taking advantage of advanced scientific computing, to face new regulations departing from deterministic design or support robust decision-making. Modelling Under Risk and Uncertainty: Addresses a concern of growing interest for large industries, environmentalists or analysts: robust modeling for decision-making in complex systems. Gives new insights into the peculiar mathematical and computational challenges generated by recent industrial safety or environmental control analysis for rare events. Implements decision theory choices differentiating or aggregating the dimensions of risk/aleatory and epistemic uncertainty through a consistent multi-disciplinary set of statistical estimation, physical modelling, robust computation and risk analysis. Provides an original review of the advanced inverse probabilistic approaches for model identification, calibration or data assimilation, key to digest fast-growing multi-physical data acquisition. Illustrated with one favourite pedagogical example crossing natural risk, engineering and economics, developed throughout the book to facilitate the reading and understanding. Supports Master/PhD-level course as well as advanced tutorials for professional training Analysts and researchers in numerical modeling, applied statistics, scientific computing, reliability, advanced engineering, natural risk or environmental science will benefit from this book.

Fundamentals of Predictive Analytics with JMP bridges the gap between courses on basic statistics, which focus on univariate and bivariate analysis, and courses on data mining/predictive analytics. This book provides the technical knowledge and problem-solving skills needed to perform real data multivariate analysis. Utilizing JMP 10 and JMP Pro, this book offers new and enhanced resources, including an add-in to Microsoft Excel, Graph Builder, and data mining capabilities.

Written for students in undergraduate and graduate statistics courses, this book first teaches students to recognize when it is appropriate to use the tool, to understand what variables and data are required, and to know what the results might be. Second, it teaches them how to interpret the results, followed by step-by-step instructions on how and where to perform and evaluate the analysis in JMP.

With the new emphasis on business intelligence, business analytics and predictive analytics, this book is invaluable to everyone who needs to expand their knowledge of statistics and apply real problem-solving analysis.

This book is part of the SAS Press program.

The only authorized guide to IBM Cognos Business Intelligence v10.1 Updated for the latest release of the software, IBM Cognos Business Intelligence 10: The Official Guide explains how to create, implement, and manage an enterprise BI solution. Maximize all of the new and enhanced features, including the powerful modeling, monitoring, and analytics capabilities. Build and deliver reports that foster informed business decisions and better results. Filled with real-world examples and expert advice, this practical resource is ideal for anyone working with IBM Cognos Business Intelligence v10.1--from administrators to end users. Monitor performance using dashboards and scorecards Assign user roles and privileges Provide a single access point to application-specific data via Cognos Connection Access content from Microsoft Office applications and mobile devices Collect and analyze BI data in an interactive dashboard with Cognos Business Insight Use Cognos Administration tools for system management Implement appropriate security measures Create BI reports with relational and dimensional data using Business Insight Advanced Use Report Studio to build dimensional reports and statistical analyses Identify and deliver mission-critical information using Event Studio Monitor business performance with Metric Studio Create, modify, organize, and publish a model in Framework Manager Ensure report integrity with Lifecycle Manager

The IBM Cognos TM1 Developer's Certification Guide is your hands-on resource to preparing for and passing the COG-310 certification exam. This book offers a practical, example-driven approach to mastering the core concepts and tools within IBM Cognos TM1, including dimension construction, scripting with Turbo Integrator, rules writing, and cube design. What this Book will help me do Master the key components and architecture of Cognos TM1 to build efficient financial models. Gain proficiency in Turbo Integrator scripting to automate data integration and transformations. Learn to create and use dimensions, cubes, and rules effectively within the TM1 environment. Understand advanced concepts like drill-through functionality, virtual cubes, and lookup cubes. Enhance your data presentation and reporting skills tailored to TM1 solutions. Author(s) James D. Miller is an experienced educator and IBM Cognos TM1 professional, with a strong background in financial and enterprise planning systems. With years of experience in the field, James brings his practical knowledge into his writing, making complex technical topics approachable and clear. He is committed to helping learners achieve their professional certifications and enhance their skill sets. Who is it for? This book is ideal for beginner to intermediate IBM Cognos TM1 developers who are looking to gain expertise in the field and obtain the COG-310 certification. If you are someone interested in enhancing your financial modeling skills and advancing your career, this guide is designed to meet your needs. It suits individuals wishing for structured, hands-on learning with practical exercises to build actual project-ready competence. Anyone aiming to independently prepare for the COG-310 certification exam will greatly benefit from this content.

An essential guide to OHSAS 18001 We say 'take care' as we wave our loved ones goodbye in the morning, but how often is this message taken into the workplace? In this easy-to-understand and timely pocket guide, Naeem Sadiq, examines the Understanda as it gears up to meet OHSAS 18001 standards of occupational health and safety. Real-world scenarios Using a wide variety of fictional 'real world' scenarios, Sadiq demonstrates the hazards that might be present in a workplace, how to assess risk, how to manage OHSAS 18001 implementation and how to communicate its implementation through all levels of management. Sadiq takes the complex, and often impenetrable, concepts that surround health and safety and presents them with absolute precision and clarity. A sound understanding of OHSAS 18001 OHSAS 18001: Step by Step is more than a primer. Besides giving the reader a sound understanding of OHSAS 18001, the pocket guide can be used as a step-by-step instructional manual for anyone tasked with implementing operational health and safety standards in the workplace. This pocket guide gives its readers: A comprehensive explanation of OHSAS 18001 and its implications An understanding of how OHSAS 18001 can be implemented through the PDCI (Plan-Do-Check-Improve) management principle A 'how-to' guide for establishing an Occupational Health and Safety (OH&S) Policy A 'how-to' guide for identifying risks and controls within the organisation An understanding of the law; the legislative and contractual OH&S requirements to which an organisation subscribes An explanation of how OH&S objectives can be determined and established, and how to apportion responsibility and accountability throughout the organisation Clear understanding of OH&S accountability and the need for diligent record-keeping A 'how-to' guide for setting up a training, competence and awareness regime Understanding of how OHSAS 18001 protects not just colleagues, but customers and contractors who enter your workplace Expert guidance on how to deal with emergencies. " Buy this pocket guide and protect your workforce with OHSAS 18001!

How statistical thinking and methodology can help you make crucial business decisions Straightforward and insightful, Statistical Thinking: Improving Business Performance, Second Edition, prepares you for business leadership by developing your capacity to apply statistical thinking to improve business processes. Unique and compelling, this book shows you how to derive actionable conclusions from data analysis, solve real problems, and improve real processes. Here, you'll discover how to implement statistical thinking and methodology in your work to improve business performance. Explores why statistical thinking is necessary and helpful Provides case studies that illustrate how to integrate several statistical tools into the decision-making process Facilitates and encourages an experiential learning environment to enable you to apply material to actual problems With an in-depth discussion of JMP® software, the new edition of this important book focuses on skills to improve business processes, including collecting data appropriate for a specified purpose, recognizing limitations in existing data, and understanding the limitations of statistical analyses.

You receive an e-mail. It contains an offer for a complete personal computer system. It seems like the retailer read your mind since you were exploring computers on their web site just a few hours prior.... As you drive to the store to buy the computer bundle, you get an offer for a discounted coffee from the coffee shop you are getting ready to drive past. It says that since you're in the area, you can get 10% off if you stop by in the next 20 minutes.... As you drink your coffee, you receive an apology from the manufacturer of a product that you complained about yesterday on your Facebook page, as well as on the company's web site.... Finally, once you get back home, you receive notice of a special armor upgrade available for purchase in your favorite online video game. It is just what is needed to get past some spots you've been struggling with.... Sound crazy? Are these things that can only happen in the distant future? No. All of these scenarios are possible today! Big data. Advanced analytics. Big data analytics. It seems you can't escape such terms today. Everywhere you turn people are discussing, writing about, and promoting big data and advanced analytics. Well, you can now add this book to the discussion. What is real and what is hype? Such attention can lead one to the suspicion that perhaps the analysis of big data is something that is more hype than substance. While there has been a lot of hype over the past few years, the reality is that we are in a transformative era in terms of analytic capabilities and the leveraging of massive amounts of data. If you take the time to cut through the sometimes-over-zealous hype present in the media, you'll find something very real and very powerful underneath it. With big data, the hype is driven by genuine excitement and anticipation of the business and consumer benefits that analyzing it will yield over time. Big data is the next wave of new data sources that will drive the next wave of analytic innovation in business, government, and academia. These innovations have the potential to radically change how organizations view their business. The analysis that big data enables will lead to decisions that are more informed and, in some cases, different from what they are today. It will yield insights that many can only dream about today. As you'll see, there are many consistencies with the requirements to tame big data and what has always been needed to tame new data sources. However, the additional scale of big data necessitates utilizing the newest tools, technologies, methods, and processes. The old way of approaching analysis just won't work. It is time to evolve the world of advanced analytics to the next level. That's what this book is about. Taming the Big Data Tidal Wave isn't just the title of this book, but rather an activity that will determine which businesses win and which lose in the next decade. By preparing and taking the initiative, organizations can ride the big data tidal wave to success rather than being pummeled underneath the crushing surf. What do you need to know and how do you prepare in order to start taming big data and generating exciting new analytics from it? Sit back, get comfortable, and prepare to find out!

Praise for the Fourth Edition "As with previous editions, the authors have produced a leading textbook on regression." —Journal of the American Statistical Association A comprehensive and up-to-date introduction to the fundamentals of regression analysis Introduction to Linear Regression Analysis, Fifth Edition continues to present both the conventional and less common uses of linear regression in today's cutting-edge scientific research. The authors blend both theory and application to equip readers with an understanding of the basic principles needed to apply regression model-building techniques in various fields of study, including engineering, management, and the health sciences. Following a general introduction to regression modeling, including typical applications, a host of technical tools are outlined such as basic inference procedures, introductory aspects of model adequacy checking, and polynomial regression models and their variations. The book then discusses how transformations and weighted least squares can be used to resolve problems of model inadequacy and also how to deal with influential observations. The Fifth Edition features numerous newly added topics, including: A chapter on regression analysis of time series data that presents the Durbin-Watson test and other techniques for detecting autocorrelation as well as parameter estimation in time series regression models Regression models with random effects in addition to a discussion on subsampling and the importance of the mixed model Tests on individual regression coefficients and subsets of coefficients Examples of current uses of simple linear regression models and the use of multiple regression models for understanding patient satisfaction data. In addition to Minitab, SAS, and S-PLUS, the authors have incorporated JMP and the freely available R software to illustrate the discussed techniques and procedures in this new edition. Numerous exercises have been added throughout, allowing readers to test their understanding of the material, and a related FTP site features the presented data sets, extensive problem solutions, software hints, and PowerPoint slides to facilitate instructional use of the book. Introduction to Linear Regression Analysis, Fifth Edition is an excellent book for statistics and engineering courses on regression at the upper-undergraduate and graduate levels. The book also serves as a valuable, robust resource for professionals in the fields of engineering, life and biological sciences, and the social sciences.

This book addresses the stochastic modeling of telecommunication networks, introducing the main mathematical tools for that purpose, such as Markov processes, real and spatial point processes and stochastic recursions, and presenting a wide list of results on stability, performances and comparison of systems. The authors propose a comprehensive mathematical construction of the foundations of stochastic network theory: Markov chains, continuous time Markov chains are extensively studied using an original martingale-based approach. A complete presentation of stochastic recursions from an ergodic theoretical perspective is also provided, as well as spatial point processes. Using these basic tools, stability criteria, performance measures and comparison principles are obtained for a wide class of models, from the canonical M/M/1 and G/G/1 queues to more sophisticated systems, including the current "hot topics" of spatial radio networking, OFDMA and real-time networks. Contents 1. Introduction. Part 1: Discrete-time Modeling 2. Stochastic Recursive Sequences. 3. Markov Chains. 4. Stationary Queues. 5. The M/GI/1 Queue. Part 2: Continuous-time Modeling 6. Poisson Process. 7. Markov Process. 8. Systems with Delay. 9. Loss Systems. Part 3: Spatial Modeling 10. Spatial Point Processes.

Get the latest information about using the #1 web analytics tool from this fully updated guide Google Analytics is the free tool used by millions of web site owners to assess the effectiveness of their efforts. Its revised interface and new features will offer even more ways to increase the value of your web site, and this book will teach you how to use each one to best advantage. Featuring new content based on reader and client requests, the book helps you implement new methods and concepts, track social and mobile visitors, use the new multichannel funnel reporting features, understand which filters to use, and much more. Gets you up and running with all the new tools in the revamped Google Analytics, and includes content requested by readers and users especially for new GA users Covers social media analytics features, advanced segmentation displays, multi-dashboard configurations, and using Top 20 reports Provides a detailed best-practices implementation guide covering advanced topics, such as how to set up GA to track dynamic web pages, banners, outgoing links, and contact forms Includes case studies and demonstrates how to optimize pay-per-click accounts, integrate AdSense, work with new reports and reporting tools, use ad version testing, and more Make your web site a more effective business tool with the detailed information and advice about Google Analytics in Advanced Web Metrics with Google Analytics, 3nd Edition.