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Praise for Modeling for Insight "Most books on modeling are either too theoretical or too focused on the mechanics of programming. Powell and Batt's emphasis on using simple spreadsheet models to gain business insight (which is, after all, the name of the game) is what makes this book stand head and shoulders above the rest. This clear and practical book deserves a place on the shelf of every business analyst." —Jonathan Koomey, PhD, Lawrence Berkeley National Laboratory and Stanford University, author of Turning Numbers into Knowledge: Mastering the Art of Problem Solving Most business analysts are familiar with using spreadsheets to organize data and build routine models. However, analysts often struggle when faced with examining new and ill-structured problems. Modeling for Insight is a one-of-a-kind guide to building effective spreadsheet models and using them to generate insights. With its hands-on approach, this book provides readers with an effective modeling process and specific modeling tools to become a master modeler. The authors provide a structured approach to problem-solving using four main steps: frame the problem, diagram the problem, build a model, and generate insights. Extensive examples, graduated in difficulty, help readers to internalize this modeling process, while also demonstrating the application of important modeling tools, including: Influence diagrams Spreadsheet engineering Parameterization Sensitivity analysis Strategy analysis Iterative modeling The real-world examples found in the book are drawn from a wide range of fields such as financial planning, insurance, pharmaceuticals, advertising, and manufacturing. Each chapter concludes with a discussion on how to use the insights drawn from these models to create an effective business presentation. Microsoft Office Excel and PowerPoint are used throughout the book, along with the add-ins Premium Solver, Crystal Ball, and Sensitivity Toolkit. Detailed appendices guide readers through the use of these software packages, and the spreadsheet models discussed in the book are available to download via the book's related Web site. Modeling for Insight is an ideal book for courses in engineering, operations research, and management science at the upper-undergraduate and graduate levels. It is also a valuable resource for consultants and business analysts who often use spreadsheets to better understand complex problems.
Familiar modes of problem solving may be efficient, but they often prevent us from discovering innovative solutions to more complex problems. To create meaningful change, we must train ourselves to discover previously unseen variables in day-to-day challenges. The Design of Insight is intended to be a personal problem-solving platform for decision makers and advisors who seek answers to critical business questions. It introduces an approach that uses multiple "problem-solving languages" to systematically expand our understanding of problem framing and high quality problem solving. Useful as a critical thinking approach or a think-out-loud document for strategic teams, this brief is a resource for enriching and implementing thoughtful management practices.
Manage and work with business data effectively by learning data modeling techniques and leveraging the latest features of Power BI Key Features Understand data modeling techniques to get the best out of data using Power BI Define the relationships between data to extract valuable insights Solve a wide variety of business challenges by building optimal data models Book DescriptionThis book is a comprehensive guide to understanding the ins and outs of data modeling and how to create data models using Power BI confidently. You'll learn how to connect data from multiple sources, understand data, define and manage relationships between data, and shape data models to gain deep and detailed insights about your organization. In this book, you'll explore how to use data modeling and navigation techniques to define relationships and create a data model before defining new metrics and performing custom calculations using modeling features. As you advance through the chapters, the book will demonstrate how to create full-fledged data models, enabling you to create efficient data models and simpler DAX code with new data modeling features. With the help of examples, you'll discover how you can solve business challenges by building optimal data models and changing your existing data models to meet evolving business requirements. Finally, you'll learn how to use some new and advanced modeling features to enhance your data models to carry out a wide variety of complex tasks. By the end of this Power BI book, you'll have gained the skills you need to structure data coming from multiple sources in different ways to create optimized data models that support reporting and data analytics.What you will learn Implement virtual tables and time intelligence functionalities in DAX to build a powerful model Identify Dimension and Fact tables and implement them in Power Query Editor Deal with advanced data preparation scenarios while building Star Schema Explore best practices for data preparation and modeling Discover different hierarchies and their common pitfalls Understand complex data models and how to decrease the level of model complexity with different approaches Learn advanced data modeling techniques such as aggregations, incremental refresh, and RLS/OLS Who this book is for This MS Power BI book is for BI users, data analysts, and analysis developers who want to become well-versed with data modeling techniques to make the most of Power BI. You’ll need a solid grasp on basic use cases and functionalities of Power BI and Star Schema functionality before you can dive in.
Insights -- like Darwin's understanding of the way evolution actually works, and Watson and Crick's breakthrough discoveries about the structure of DNA -- can change the world. We also need insights into the everyday things that frustrate and confuse us so that we can more effectively solve problems and get things done. Yet we know very little about when, why, or how insights are formed -- or what blocks them. In Seeing What Others Don't, renowned cognitive psychologist Gary Klein unravels the mystery. Klein is a keen observer of people in their natural settings -- scientists, businesspeople, firefighters, police officers, soldiers, family members, friends, himself -- and uses a marvelous variety of stories to illuminate his research into what insights are and how they happen. What, for example, enabled Harry Markopolos to put the finger on Bernie Madoff? How did Dr. Michael Gottlieb make the connections between different patients that allowed him to publish the first announcement of the AIDS epidemic? What did Admiral Yamamoto see (and what did the Americans miss) in a 1940 British attack on the Italian fleet that enabled him to develop the strategy of attack at Pearl Harbor? How did a "smokejumper" see that setting another fire would save his life, while those who ignored his insight perished? How did Martin Chalfie come up with a million-dollar idea (and a Nobel Prize) for a natural flashlight that enabled researchers to look inside living organisms to watch biological processes in action? Klein also dissects impediments to insight, such as when organizations claim to value employee creativity and to encourage breakthroughs but in reality block disruptive ideas and prioritize avoidance of mistakes. Or when information technology systems are "dumb by design" and block potential discoveries. Both scientifically sophisticated and fun to read, Seeing What Others Don't shows that insight is not just a "eureka!" moment but a whole new way of understanding.
Growth models are among the core methods for analyzing how and when people change. Discussing both structural equation and multilevel modeling approaches, this book leads readers step by step through applying each model to longitudinal data to answer particular research questions. It demonstrates cutting-edge ways to describe linear and nonlinear change patterns, examine within-person and between-person differences in change, study change in latent variables, identify leading and lagging indicators of change, evaluate co-occurring patterns of change across multiple variables, and more. User-friendly features include real data examples, code (for Mplus or NLMIXED in SAS, and OpenMx or nlme in R), discussion of the output, and interpretation of each model's results. User-Friendly Features *Real, worked-through longitudinal data examples serving as illustrations in each chapter. *Script boxes that provide code for fitting the models to example data and facilitate application to the reader's own data. *"Important Considerations" sections offering caveats, warnings, and recommendations for the use of specific models. *Companion website supplying datasets and syntax for the book's examples, along with additional code in SAS/R for linear mixed-effects modeling.
Provides a unique and methodologically consistent treatment of various areas of fuzzy modeling and includes the results of mathematical fuzzy logic and linguistics This book is the result of almost thirty years of research on fuzzy modeling. It provides a unique view of both the theory and various types of applications. The book is divided into two parts. The first part contains an extensive presentation of the theory of fuzzy modeling. The second part presents selected applications in three important areas: control and decision-making, image processing, and time series analysis and forecasting. The authors address the consistent and appropriate treatment of the notions of fuzzy sets and fuzzy logic and their applications. They provide two complementary views of the methodology, which is based on fuzzy IF-THEN rules. The first, more traditional method involves fuzzy approximation and the theory of fuzzy relations. The second method is based on a combination of formal fuzzy logic and linguistics. A very important topic covered for the first time in book form is the fuzzy transform (F-transform). Applications of this theory are described in separate chapters and include image processing and time series analysis and forecasting. All of the mentioned components make this book of interest to students and researchers of fuzzy modeling as well as to practitioners in industry. Features: Provides a foundation of fuzzy modeling and proposes a thorough description of fuzzy modeling methodology Emphasizes fuzzy modeling based on results in linguistics and formal logic Includes chapters on natural language and approximate reasoning, fuzzy control and fuzzy decision-making, and image processing using the F-transform Discusses fuzzy IF-THEN rules for approximating functions, fuzzy cluster analysis, and time series forecasting Insight into Fuzzy Modeling is a reference for researchers in the fields of soft computing and fuzzy logic as well as undergraduate, master and Ph.D. students. Vilém Novák, D.Sc. is Full Professor and Director of the Institute for Research and Applications of Fuzzy Modeling, University of Ostrava, Czech Republic. Irina Perfilieva, Ph.D. is Full Professor, Senior Scientist, and Head of the Department of Theoretical Research at the Institute for Research and Applications of Fuzzy Modeling, University of Ostrava, Czech Republic. Antonín Dvorák, Ph.D. is Associate Professor, and Senior Scientist at the Institute for Research and Applications of Fuzzy Modeling, University of Ostrava, Czech Republic.
Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence, Second Edition, provides a synthesis of model-based approaches for analyzing presence-absence data, allowing for imperfect detection. Beginning from the relatively simple case of estimating the proportion of area or sampling units occupied at the time of surveying, the authors describe a wide variety of extensions that have been developed since the early 2000s. This provides an improved insight about species and community ecology, including, detection heterogeneity; correlated detections; spatial autocorrelation; multiple states or classes of occupancy; changes in occupancy over time; species co-occurrence; community-level modeling, and more. Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence, Second Edition has been greatly expanded and detail is provided regarding the estimation methods and examples of their application are given. Important study design recommendations are also covered to give a well rounded view of modeling. - Provides authoritative insights into the latest in occupancy modeling - Examines the latest methods in analyzing detection/no detection data surveys - Addresses critical issues of imperfect detectability and its effects on species occurrence estimation - Discusses important study design considerations such as defining sample units, sample size determination and optimal effort allocation
What do winners of major sales do differently than the sellers who almost won, but ultimately came in second place? Mike Schultz and John Doerr, bestselling authors and world-renowned sales experts, set out to find the answer. They studied more than 700 business-to-business purchases made by buyers who represented a total of $3.1 billion in annual purchasing power. When they compared the winners to the second-place finishers, they found surprising results. Not only do sales winners sell differently, they sell radically differently, than the second-place finishers. In recent years, buyers have increasingly seen products and services as replaceable. You might think this would mean that the sale goes to the lowest bidder. Not true! A new breed of seller—the insight seller—is winning the sale with strong prices and margins even in the face of increasing competition and commoditization. In Insight Selling, Schultz and Doerr share the surprising results of their research on what sales winners do differently, and outline exactly what you need to do to transform yourself and your team into insight sellers. They introduce a simple three-level model based on what buyers say tip the scales in favor of the winners: Level 1 "Connect." Winners connect the dots between customer needs and company solutions, while also connecting with buyers as people. Level 2 "Convince." Winners convince buyers that they can achieve maximum return, that the risks are acceptable, and that the seller is the best choice among all options. Level 3 "Collaborate." Winners collaborate with buyers by bringing new ideas to the table, delivering new ideas and insights, and working with buyers as a team. They also found that much of the popular and current advice given to sellers can damage sales results. Insight Selling is both a strategic and tactical guide that will separate the good advice from the bad, and teach you how to put the three levels of selling to work to inspire buyers, influence their agendas, and maximize value. If you want to find yourself and your team in the winner's circle more often, this book is a must-read.
Research on insight problem solving examines how new ideas are generated to solve problems that initially resist the application of prior knowledge or analogue solutions. In the laboratory, insight problems are designed to create an impasse; overcoming the impasse is sometimes accompanied by a distinctive phenomenological experience, the so-called Aha! moment. Insight: On the Origins of New Ideas presents research that captures these episodes of insight under laboratory conditions and informs models that account for their emergence. Descriptions and analyses of episodes of discovery both in and out of the laboratory are included to provide a general overview of insight. Featuring contributions from leading researchers, the volume debates the relative importance of intelligence and working memory, the development of an alternative interpretation of the problem based on deliberate analyses and heuristics, and unconscious inferences in the emergence of insight. These discussions generate new testable hypotheses to shed light on the cognitive processes underpinning insight, along with concrete methodological recommendations that, together, map a productive programme of future research. This book will be of interest to students and researchers of thinking and reasoning - specifically those interested in insight and creative problem solving.
This unified modeling textbook for students of biomedical engineering provides a complete course text on the foundations, theory and practice of modeling and simulation in physiology and medicine. It is dedicated to the needs of biomedical engineering and clinical students, supported by applied BME applications and examples. Developed for biomedical engineering and related courses: speaks to BME students at a level and in a language appropriate to their needs, with an interdisciplinary clinical/engineering approach, quantitative basis, and many applied examples to enhance learning Delivers a quantitative approach to modeling and also covers simulation: the perfect foundation text for studies across BME and medicine Extensive case studies and engineering applications from BME, plus end-of-chapter exercises