A straightforward, full-color guide to showcasing data so your audience can see what you mean, not just read about it Big data is big news! Every company, industry, not-for-profit, and government agency wants and needs to analyze and leverage datasets that can quickly become ponderously large. Data visualization software enables different industries to present information in ways that are memorable and relevant to their mission. This full-color guide introduces you to a variety of ways to handle and synthesize data in much more interesting ways than mere columns and rows of numbers. Learn meaningful ways to show trending and relationships, how to convey complex data in a clear, concise diagram, ways to create eye-catching visualizations, and much more! Effective data analysis involves learning how to synthesize data, especially big data, into a story and present that story in a way that resonates with the audience This full-color guide shows you how to analyze large amounts of data, communicate complex data in a meaningful way, and quickly slice data into various views Explains how to automate redundant reporting and analyses, create eye-catching visualizations, and use statistical graphics and thematic cartography Enables you to present vast amounts of data in ways that won't overwhelm your audience Part technical manual and part analytical guidebook, Data Visualization For Dummies is the perfect tool for transforming dull tables and charts into high-impact visuals your audience will notice...and remember.

This book, "QlikView Server and Publisher," serves as a comprehensive guide for implementing and managing QlikView Server and Publisher in enterprise environments. It walks you through the entire process, highlighting vital configuration techniques, and best practices necessary to maximize the potential of QlikView for your data solutions. What this Book will help me do Understand the best practices for configuring QlikView Server and Publisher in your organization's IT environment. Master the process of installing and maintaining QlikView Server to ensure optimal performance. Learning how to deploy enterprise-grade QlikView Server setups effectively. Gain expertise in setting up and leveraging QlikView Publisher for task scheduling and automation. Acquire the skills to integrate QlikView with advanced security solutions and monitor system efficiency. Author(s) Stephen Redmond is a renowned author and expert on data visualization platforms, particularly QlikView. With years of experience in implementing enterprise data solutions, Stephen brings practical insights to complex technical concepts. He focuses on guiding readers with systematic and approachable methods to master Qlik technologies. Who is it for? This book is designed for IT professionals and system administrators who are tasked with deploying or maintaining QlikView systems. Whether you're new to QlikView or have some experience, you'll find the material clear and beneficial to mastering enterprise implementations. The content suits individuals aiming to improve data-driven decision-making systems in their organization.

Many analysts are too concerned with tools and techniques for cleansing, modeling, and visualizing datasets and not concerned enough with asking the right questions. In this practical guide, data strategy consultant Max Shron shows you how to put the why before the how, through an often-overlooked set of analytical skills. Thinking with Data helps you learn techniques for turning data into knowledge you can use. You’ll learn a framework for defining your project, including the data you want to collect, and how you intend to approach, organize, and analyze the results. You’ll also learn patterns of reasoning that will help you unveil the real problem that needs to be solved. Learn a framework for scoping data projects Understand how to pin down the details of an idea, receive feedback, and begin prototyping Use the tools of arguments to ask good questions, build projects in stages, and communicate results Explore data-specific patterns of reasoning and learn how to build more useful arguments Delve into causal reasoning and learn how it permeates data work Put everything together, using extended examples to see the method of full problem thinking in action

This new business analytics case study challenges readers to forecast donations, plan budgets, and manage cash flow for a religious institution suffering rapidly falling contributions. Crystallizing realistic analytical challenges faced by non-profit and for-profit organizations of all kinds, it exposes readers to the entire decision-making process, providing opportunities to perform analyses, interpret output, and recommend the best course of action. Author: Matthew J. Drake, Duquesne University.

This new business analytics case study challenges readers to project trends and plan capacity for a fast-growing craft beer operation, so it can make the best possible decisions about expensive investments in brewing capacity. Crystallizing realistic analytical challenges faced by companies in many industries and markets, it exposes readers to the entire decision-making process, providing opportunities to perform analyses, interpret output, and recommend the best course of action. Author: Eric Huggins, Fort Lewis College.

Many areas of mining engineering gather and use statistical information, provided by observing the actual operation of equipment, their systems, the development of mining works, surface subsidence that accompanies underground mining, displacement of rocks surrounding surface pits and underground drives and longwalls, amongst others. In addition, the actual modern machines used in surface mining are equipped with diagnostic systems that automatically trace all important machine parameters and send this information to the main producer’s computer. Such data not only provide information on the technical properties of the machine but they also have a statistical character. Furthermore, all information gathered during stand and lab investigations where parts, assemblies and whole devices are tested in order to prove their usefulness, have a stochastic character. All of these materials need to be developed statistically and, more importantly, based on these results mining engineers must make decisions whether to undertake actions, connected with the further operation of the machines, the further development of the works, etc. For these reasons, knowledge of modern statistics is necessary for mining engineers; not only as to how statistical analysis of data should be conducted and statistical synthesis should be done, but also as to understanding the results obtained and how to use them to make appropriate decisions in relation to the mining operation. This book on statistical analysis and synthesis starts with a short repetition of probability theory and also includes a special section on statistical prediction. The text is illustrated with many examples taken from mining practice; moreover the tables required to conduct statistical inference are included.

Features recent trends and advances in the theory and techniques used to accurately measure and model growth Growth Curve Modeling: Theory and Applications features an accessible introduction to growth curve modeling and addresses how to monitor the change in variables over time since there is no "one size fits all" approach to growth measurement. A review of the requisite mathematics for growth modeling and the statistical techniques needed for estimating growth models are provided, and an overview of popular growth curves, such as linear, logarithmic, reciprocal, logistic, Gompertz, Weibull, negative exponential, and log-logistic, among others, is included. In addition, the book discusses key application areas including economic, plant, population, forest, and firm growth and is suitable as a resource for assessing recent growth modeling trends in the medical field. SAS is utilized throughout to analyze and model growth curves, aiding readers in estimating specialized growth rates and curves. Including derivations of virtually all of the major growth curves and models, Growth Curve Modeling: Theory and Applications also features: Statistical distribution analysis as it pertains to growth modeling Trend estimations Dynamic site equations obtained from growth models Nonlinear regression Yield-density curves Nonlinear mixed effects models for repeated measurements data Growth Curve Modeling: Theory and Applications is an excellent resource for statisticians, public health analysts, biologists, botanists, economists, and demographers who require a modern review of statistical methods for modeling growth curves and analyzing longitudinal data. The book is also useful for upper-undergraduate and graduate courses on growth modeling.

MATLAB for Neuroscientists serves as the only complete study manual and teaching resource for MATLAB, the globally accepted standard for scientific computing, in the neurosciences and psychology. This unique introduction can be used to learn the entire empirical and experimental process (including stimulus generation, experimental control, data collection, data analysis, modeling, and more), and the 2nd Edition continues to ensure that a wide variety of computational problems can be addressed in a single programming environment. This updated edition features additional material on the creation of visual stimuli, advanced psychophysics, analysis of LFP data, choice probabilities, synchrony, and advanced spectral analysis. Users at a variety of levels—advanced undergraduates, beginning graduate students, and researchers looking to modernize their skills—will learn to design and implement their own analytical tools, and gain the fluency required to meet the computational needs of neuroscience practitioners. The first complete volume on MATLAB focusing on neuroscience and psychology applications Problem-based approach with many examples from neuroscience and cognitive psychology using real data Illustrated in full color throughout Careful tutorial approach, by authors who are award-winning educators with strong teaching experience

Bistatic radar consists of a radar system which comprises a transmitter and receiver which are separated by a distance comparable to the expected target distance. This book provides a general theoretical description of such bistatic technology in the context of synthetic aperture, inverse synthetic aperture and forward scattering radars from the point of view of analytical geometrical and signal formation as well as processing theory. Signal formation and image reconstruction algorithms are developed with the application of high informative linear frequency and phase code modulating techniques, and numerical experiments that confirm theoretical models are carried out. The authors suggest the program implementation of developed algorithms. A theoretical summary of the latest results in the field of bistatic radars is provided, before applying an analytical geometrical description of scenarios of bistatic synthetic aperture, inverse synthetic aperture and forward scattering radars with cooperative and non-cooperative transmitters. Signal models with linear frequency and phase code modulation are developed, and special phase modulations with C/A (coarse acquisition) and P (precision) of GPS satellite transmitters are considered. The authors suggest Matlab implementations of all geometrical models and signal formation and processing algorithms. Contents 1. Bistatic Synthetic Aperture Radar (BSAR) Survey. 2. BSAR Geometry. 3. BSAR Waveforms and Signal Models. 4. BSAR Image Reconstruction Algorithms. 5. Analytical Geometrical Determination of BSAR Resolution. 6. BSAR Experimental Results. 7. BSAR Matlab Implementation. A general theoretical description of bistatic technology within the scope of synthetic aperture, inverse synthetic aperture and forward scattering radars from the point of view of analytical geometrical and signal formation and processing theory. Signal formation and image reconstruction algorithms are developed in this title, with application of high informative linear frequency and phase code modulating techniques. Numerical experiments that confirm theoretical models are carried out and the authors suggest program implementation for the algorithms developed.

During the Cold War, various intelligence programs were created to acquire the information needed for effective defense planning. Among them were programs of aerial reconnaissance to collect both photographic intelligence and signals intelligence.

MATLAB ® provides an interactive programming interface for numerical computation and data visualization making it the default framework used for analysis, design and research in many domains of science and industry. Programming in MATLAB ®: A problem-solving approach is intended as an aid to engineers and scientists with no prior programming expertise. The book focuses on the systematic development of practical programming skills through MATLAB language constructs, backed by several well-designed examples and exercises. Designed to be as much a MATLAB reference tool for researchers in varied fields as it is a guide for undergraduate readers, the book builds on the concepts sequentially as it progresses through the chapters. Each chapter is complete, independent of the book's remaining contents. Thus, for teaching purposes, one can suitably the relevant portions.

Over the last decade Lean and Six Sigma methods and tools have helped organizations improve to historic productivity levels with the data driven, systematic elimination of waste and improvement of flow. Today many organizations have enjoyed the benefits of Lean and Six sigma initiatives, and are looking more to sustain the gains, and aggressively drive a systematic and on-going approach to improvement and problem solving. The concept of diminishing returns applies here, when in the early stages, organizations were able to find "low-hanging fruit" and to quickly make significant improvements. Now the easy work is done, and organizations need a simple yet systematic approach to continuing their continuous improvement efforts. Operations and supply chain leaders will benefit from this book by developing a clear understanding of why and how metric scorecards and dashboards can be used as a powerful data driven improvement tool. This book illustrates visual management, scorecards, and dashboards for a full range of organizations, and focuses on Operations and Supply Chain Management areas. By covering these tools in these environments in a story book format, organization leaders can begin to understand how these methods and tools can be applied in their organizations.

Tired of boring spreadsheets and data overload from confusing graphs? Master the art of visualization with Rapid Graphs with Tableau 8! Tableau insiders Stephen and Eileen McDaniel expertly provide a hands-on case study approach and more than 225 illustrations that will teach you how to quickly explore and understand your data to make informed decisions in a wide variety of real-world situations. Rapid Graphs with Tableau 8 includes best practices of visual analytics for ideas on how to communicate your findings with audience-friendly graphs, tables and maps. "A picture is worth a thousand words" is a common saying that is more relevant today than ever as data volumes grow and the need for easy access to answers becomes more critical. This book covers the core of Tableau capabilities in easy-to-follow examples, updated and expanded for Version 8. Learn how to be successful with Tableau from the team that started the original training program as the founding Tableau Education Partner! "A must read for anyone interested in Tableau. Clear explanations, practical advice and beautiful examples!" Elissa Fink – Chief Marketing Officer, Tableau Software What you'll learn Connect to and review data visually Create insightful maps and take advantage of view shifting Understand the types of views available in Tableau Take advantage of the powerful Marks card and much more Who this book is for Rapid Graphs with Tableau 8 is a great resource for those new to Tableau, and also contains useful tips and tricks for advanced users as well.

PROC REPORT by Example: Techniques for Building Professional Reports Using SAS provides real-world examples using PROC REPORT to create a wide variety of professional reports. Written from the point of view of the programmer who produces the reports, this book explains and illustrates creative techniques used to achieve the desired results.

Each chapter focuses on a different concrete example, shows an image of the final report, and then takes you through the process of creating that report. You will be able to break each report down to find out how it was produced, including any data manipulation you have to do.

The book clarifies solutions to common, everyday programming challenges and typical daily tasks that programmers encounter. For example: obtaining desired report formats using style templates supplied by SAS and PROC TEMPLATE, PROC REPORT STYLE options, and COMPUTE block features employing different usage options (DISPLAY, ORDER, GROUP, ANALYSIS, COMPUTED) to create a variety of detail and summary reports using BREAK statements and COMPUTE blocks to summarize and report key findings producing reports in various Output Delivery System (ODS) destinations including RTF, PDF, XML, TAGSETS.RTF embedding images in a report and combining graphical and tabular data with SAS 9.2 and beyond

Applicable to SAS users from all disciplines, the real-life scenarios will help elevate your reporting skills learned from other books to the next level.

With PROC REPORT by Example: Techniques for Building Professional Reports Using SAS, what seemed complex will become a matter of practice.

This book is part of the SAS Press program.

This book explains how to use business analytics to sort through an ever-increasing amount of data and improve the decision-making capabilities of an organization. Covering the key areas of business analytics, the book explores the concepts, techniques, applications, and emerging trends that professionals across a wide range of industries need to be aware of. It also examines legal and privacy issues and explores social media in analytics. With this book, readers can develop the understanding required to use Big Data and high-performance computing in complex environments to improve strategic decision making.

New Tools to Solve Your Option Pricing Problems For nonlinear PDEs encountered in quantitative finance, advanced probabilistic methods are needed to address dimensionality issues. Written by two leaders in quantitative research—including Risk magazine’s 2013 Quant of the Year— Nonlinear Option Pricing compares various numerical methods for solving high-dimensional nonlinear problems arising in option pricing. Designed for practitioners, it is the first authored book to discuss nonlinear Black-Scholes PDEs and compare the efficiency of many different methods. Real-World Solutions for Quantitative Analysts The book helps quants develop both their analytical and numerical expertise. It focuses on general mathematical tools rather than specific financial questions so that readers can easily use the tools to solve their own nonlinear problems. The authors build intuition through numerous real-world examples of numerical implementation. Although the focus is on ideas and numerical examples, the authors introduce relevant mathematical notions and important results and proofs. The book also covers several original approaches, including regression methods and dual methods for pricing chooser options, Monte Carlo approaches for pricing in the uncertain volatility model and the uncertain lapse and mortality model, the Markovian projection method and the particle method for calibrating local stochastic volatility models to market prices of vanilla options with/without stochastic interest rates, the a + bλ technique for building local correlation models that calibrate to market prices of vanilla options on a basket, and a new stochastic representation of nonlinear PDE solutions based on marked branching diffusions.

Learn the theory behind and methods for predictive modeling using SAS Enterprise Miner.

Learn how to produce predictive models and prepare presentation-quality graphics in record time with Predictive Modeling with SAS Enterprise Miner: Practical Solutions for Business Applications, Second Edition.

If you are a graduate student, researcher, or statistician interested in predictive modeling; a data mining expert who wants to learn SAS Enterprise Miner; or a business analyst looking for an introduction to predictive modeling using SAS Enterprise Miner, you'll be able to develop predictive models quickly and effectively using the theory and examples presented in this book.

Author Kattamuri Sarma offers the theory behind, programming steps for, and examples of predictive modeling with SAS Enterprise Miner, along with exercises at the end of each chapter. You'll gain a comprehensive awareness of how to find solutions for your business needs. This second edition features expanded coverage of the SAS Enterprise Miner nodes, now including File Import, Time Series, Variable Clustering, Cluster, Interactive Binning, Principal Components, AutoNeural, DMNeural, Dmine Regression, Gradient Boosting, Ensemble, and Text Mining.

Develop predictive models quickly, learn how to test numerous models and compare the results, gain an in-depth understanding of predictive models and multivariate methods, and discover how to do in-depth analysis. Do it all with Predictive Modeling with SAS Enterprise Miner.

This book is part of the SAS Press program.

Statistical Computation for Programmers, Scientists, Quants, Excel Users, and Other Professionals Using the open source R language, you can build powerful statistical models to answer many of your most challenging questions. R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone is the solution. Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you’ll need to accomplish 80 percent of modern data tasks. Lander’s self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You’ll download and install R; navigate and use the R environment; master basic program control, data import, and manipulation; and walk through several essential tests. Then, building on this foundation, you’ll construct several complete models, both linear and nonlinear, and use some data mining techniques. By the time you’re done, you won’t just know how to write R programs, you’ll be ready to tackle the statistical problems you care about most. COVERAGE INCLUDES • Exploring R, RStudio, and R packages • Using R for math: variable types, vectors, calling functions, and more • Exploiting data structures, including data.frames, matrices, and lists • Creating attractive, intuitive statistical graphics • Writing user-defined functions • Controlling program flow with if, ifelse, and complex checks • Improving program efficiency with group manipulations • Combining and reshaping multiple datasets • Manipulating strings using R’s facilities and regular expressions • Creating normal, binomial, and Poisson probability distributions • Programming basic statistics: mean, standard deviation, and t-tests • Building linear, generalized linear, and nonlinear models • Assessing the quality of models and variable selection • Preventing overfitting, using the Elastic Net and Bayesian methods • Analyzing univariate and multivariate time series data • Grouping data via K-means and hierarchical clustering • Preparing reports, slideshows, and web pages with knitr • Building reusable R packages with devtools and Rcpp • Getting involved with the R global community

Contains the complete reference for all Base SAS procedures. Provides information about what each procedure does and, if relevant, the kind of output that it produces.

With 34 new contributors, this best-selling handbook provides comprehensive coverage of the main topics in pure and applied graph theory. This second edition incorporates 14 new sections. Each chapter includes lists of essential definitions and facts, accompanied by examples, tables, remarks, and, in some cases, conjectures and open problems.