This book explores the ways in which statistical models, methods, and research designs can be used to open new possibilities for APC analysis. Within a single, consistent HAPC-GLMM statistical modeling framework, the authors synthesize APC models and methods for three research designs: age-by-time period tables of population rates or proportions, repeated cross-section sample surveys, and accelerated longitudinal panel studies. They show how the empirical application of the models to various problems leads to many fascinating findings on how outcome variables develop along the age, period, and cohort dimensions.

Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in changing environments, including economic, environmental, and social data. This volume presents novel methodologies for automatically processing these types of data to support rational decision making for sustainable development. Through numerous case studies and applications, it illustrates important data analysis methods, including mathematical optimization, machine learning, signal processing, and temporal and spatial analysis, for quantifying and describing sustainable development problems.

This book shows how constrained principal component analysis (CPCA) offers a unified framework for regression techniques and PCA. Keeping the use of complicated iterative methods to a minimum, the book includes implementation details and many real application examples. It also offers material for methodologically oriented readers interested in developing statistical techniques of their own. MATLAB programs as well as data to create the book's examples are available on the author's website.

This work collects recent results from this specialized area of data mining that have previously been scattered in the literature, making them more accessible to researchers and developers in data mining and other fields. The book not only presents concepts and techniques for contrast data mining, but also explores the use of contrast mining to solve challenging problems in various scientific, medical, and business domains. It examines how contrast mining is used in discriminative gene transfer and microarray analysis, computational toxicology, spatial and image data classification, network security, and many more applications.

A self-contained, systematic introduction, this book shows you how to draw valid statistical inferences from survey data with sensitive characteristics. It guides you in applying the non-randomized response approach in surveys and new non-randomized response designs. The techniques covered integrate the strengths of existing approaches, including randomized response models, incomplete categorical data design, the EM algorithm, the bootstrap method, and the data augmentation algorithm. All R codes for the examples are available online.

While numerous advanced statistical approaches have recently been developed for quantitative trait loci (QTL) mapping, the methods are scattered throughout the literature. This book brings together many recent statistical techniques that address the data complexity of QTL mapping. It emphasizes the modern statistical methodology for QTL mapping as well as the statistical issues that arise during this process. The book gives the necessary biological background for statisticians without training in genetics and, likewise, covers statistical thinking and principles for geneticists.

Developed from the esteemed author's advanced undergraduate and graduate courses at the University of Cambridge, this text provides a hands-on, sound introduction to mathematical finance. Assuming no prior knowledge of stochastic calculus or measure-theoretic probability, the author includes the relevant mathematical background as well as many exercises with solutions. He first presents the classical topics of utility and the mean-variance approach to portfolio choice. Focusing on derivative pricing, the text then covers the binomial model, the general discrete-time model, Brownian motion, the Black-Scholes model, and various interest-rate models.

By discussing statistical concepts in the context of transportation planning and operations, this text provides the necessary background for making informed transportation-related decisions. It explains the why behind standard methods and uses real-world transportation examples and problems to illustrate key concepts. The book covers the statistical techniques most frequently employed by transportation and pavement professionals. To familiarize readers with the underlying theory and equations, it contains problems that can be solved using SAS's JMP package, which enables users to interactively explore and visualize data.

Gnuplot in Action, Second Edition is a major revision of this popular and authoritative guide for developers, engineers, and scientists who want to learn and use gnuplot effectively. Fully updated for gnuplot version 5, the book includes four pages of color illustrations and four bonus appendixes available in the eBook. About the Technology Gnuplot is an open-source graphics program that helps you analyze, interpret, and present numerical data. Available for Unix, Mac, and Windows, it is well-maintained, mature, and totally free. About the Book Gnuplot in Action, Second Edition is a major revision of this authoritative guide for developers, engineers, and scientists. The book starts with a tutorial introduction, followed by a systematic overview of gnuplot's core features and full coverage of gnuplot's advanced capabilities. Experienced readers will appreciate the discussion of gnuplot 5?s features, including new plot types, improved text and color handling, and support for interactive, web-based display formats. The book concludes with chapters on graphical effects and general techniques for understanding data with graphs. It includes four pages of color illustrations. 3D graphics, false-color plots, heatmaps, and multivariate visualizations are covered in chapter-length appendixes available in the eBook. What's Inside Creating different types of graphs in detail Animations, scripting, batch operations Extensive discussion of terminals Updated to cover gnuplot version 5 About the Reader No prior experience with gnuplot is required. This book concentrates on practical applications of gnuplot relevant to users of all levels. About the Author Philipp K. Janert, Ph.D, is a programmer and scientist. He is the author of several books on data analysis and applied math and has been a gnuplot power user and developer for over 20 years. Quotes The highly anticipated, updated version of my go-to-for-everything book on gnuplot. - Ryan Balfanz, Shift Medical, Inc. The essential guide for newcomers and the definitive handbook for advanced users. - Zoltán Vörös, University of Innsbruck Learn how to use gnuplot to convert meaningful data into attention-grabbing visualizations that communicate your message quickly and accurately. - David Kerns, Rincon Research Corporation An accessible guide to gnuplot and best practices of everyday data visualization. - Wesley R. Elsberry,PhD, RealPage, Inc.

"If you need more traffic, leads and sales, you need The Conversion Code." "We've helped 11,000+ businesses generate more than 31 million leads and consider The Conversion Code a must read." Neil Patel co-founder Crazy Egg "We'd been closing 55% of our qualified appointments. We increased that to 76% as a direct result of implementing The Conversion Code." Oli Gardner co-founder Unbounce "The strategies in The Conversion Code are highly effective and immediately helped our entire sales team. The book explains the science behind selling in a way that is simple to remember and easy to implement." Dan Stewart CEO Happy Grasshopper Steve Pacinelli CMO BombBomb Capture and close more Internet leads with a new sales script and powerful marketing templates The Conversion Code provides a step-by-step blueprint for increasing sales in the modern, Internet-driven era. Today's consumers are savvy, and they have more options than ever before. Capturing their attention and turning it into revenue requires a whole new approach to marketing and sales. This book provides clear guidance toward conquering the new paradigm shift towards online lead generation and inside sales. You'll learn how to capture those invaluable Internet leads, convert them into appointments, and close more deals. Regardless of product or industry, this proven process will increase both the quantity and quality of leads and put your sales figures on the rise. Traditional sales and marketing advice is becoming less and less relevant as today's consumers are spending much more time online, and salespeople are calling, emailing, and texting leads instead of meeting them in person. This book shows you where to find them, how to engage them, and how to position your company as the ideal solution to their needs. The business world is moving away from "belly-to-belly" interactions and traditional advertising. Companies are forced to engage with prospective customers first online—the vast majority through social media, mobile apps, blogs, and live chat—before ever meeting in person. Yesterday's marketing advice no longer applies to today's tech savvy, mobile-first, social media-addicted consumer, and the new sales environment demands that you meet consumers where they are and close them, quickly. The Conversion Code gives you an actionable blueprint for capturing Internet leads and turning them into customers. Engage with consumers more effectively online Leverage the strengths of social media, apps, and blogs to capture more leads for less money Convert more Internet leads into real-world prospects and sales appointments Make connections on every call and learn the exact words that close more sales

Embark on a journey to create stunning web-based 3D applications and games using Babylon.js, a powerful JavaScript framework. This essentials book takes you from the ground up, teaching the theory and practical applications of 3D development, with a particular focus on ease and accessibility. By the end of this guide, you'll possess the skills to design and implement dynamic 3D experiences. What this Book will help me do Gain a fundamental understanding of TypeScript and its advantages in large-scale projects like 3D engines. Master the foundational principles of 3D development with Babylon.js, emphasized through hands-on practice and clear theory. Learn to apply materials in Babylon.js, enabling you to alter and enrich the visual appeal of 3D objects. Incorporate collision physics and gameplay dynamics by understanding essential concepts like impostors in 3D simulations. Utilize advanced Babylon.js features, such as 3D audio spatialization and rendering post-process effects, to create immersive experiences. Author(s) None Moreau-Mathis, a software developer with significant experience, has worked on developing cutting-edge applications at companies like Microsoft. Their expertise in 3D development frameworks, particularly Babylon.js, has enabled them to break down complex technical concepts into approachable lessons. Moreau-Mathis combines a passion for sharing knowledge with years of hands-on experience to provide readers with practical and inspirational advice. Who is it for? This book is perfect for developers familiar with HTML5 and seeking to begin 3D Web application and game development using Babylon.js. Readers should have basic programming knowledge, such as in Object-Oriented Programming, and familiarity with web development concepts to grasp framework architecture effectively. Whether you are enhancing your web development toolkit or starting out with 3D, this book will help you achieve your aims.

Dive into the world of regression analysis guided by Python in this comprehensive book. From simple linear regression to complex models, you'll gain a deep understanding of how to analyze data and predict outcomes. By the end of this book, you will be equipped with the skills to tidy data, build models, and apply regression techniques to real-world problems. What this Book will help me do Understand and format datasets to prepare them for regression analysis efficiently. Build and implement various regression models, such as linear and logistic regression, to solve data science problems. Develop techniques to combat overfitting and ensure predictive accuracy. Learn to scale and adapt regression models to large datasets and apply incremental learning. Apply the skills gained to make informed business decisions using predictive insights from regression models. Author(s) Luca Massaron and Alberto Boschetti are seasoned data professionals with years of expertise in data science, regression analysis, and Python programming. They are passionate about teaching and have crafted this book to demystify regression for learners interested in predictive analytics. Their approachable style ensures concepts are accessible yet comprehensive. Who is it for? This book is ideal for Python developers and data scientists who have a foundational knowledge of math and statistics. Whether you're looking to delve deeper into predictive modeling or efficiently analyze datasets, this book provides step-by-step guidance. If you've dabbled in data science and wish to expand your skillset to include regression analysis, this book is for you!

How do you take your data analysis skills beyond Excel to the next level? By learning just enough Python to get stuff done. This hands-on guide shows non-programmers like you how to process information that’s initially too messy or difficult to access. You don't need to know a thing about the Python programming language to get started. Through various step-by-step exercises, you’ll learn how to acquire, clean, analyze, and present data efficiently. You’ll also discover how to automate your data process, schedule file- editing and clean-up tasks, process larger datasets, and create compelling stories with data you obtain. Quickly learn basic Python syntax, data types, and language concepts Work with both machine-readable and human-consumable data Scrape websites and APIs to find a bounty of useful information Clean and format data to eliminate duplicates and errors in your datasets Learn when to standardize data and when to test and script data cleanup Explore and analyze your datasets with new Python libraries and techniques Use Python solutions to automate your entire data-wrangling process

This book dives into the practical application of R's power combined with Shiny's simplicity to build web-based analytics and interactive data summary tools. By following this step-by-step guide, you'll go from the basics of building with R and Shiny to creating sophisticated custom dashboards and interactive web apps. What this Book will help me do Create interactive web apps and dashboards using Shiny with impressive user interfaces. Integrate Shiny applications into custom HTML and CSS-based web pages for enhanced flexibility. Produce user-friendly Shiny applications extended with JavaScript and jQuery for added functionality. Develop web solutions that include interactive graphics, maps, and data analysis summaries. Deliver and deploy web apps securely using cloud solutions or self-hosted servers. Author(s) Chris Beeley, an experienced R developer and teacher, has a robust background in statistical programming and data analysis. Chris is passionate about sharing knowledge through practical examples and hands-on exercises. As the author of this book, Chris ensures that readers receive a clear and approachable entry into web application development using Shiny. Who is it for? This book is ideal for data enthusiasts, analysts, and developers looking to transition their analytic skills to the web. It caters to readers with basic programming knowledge but does not require prior experience with R or Shiny. It is perfect for professionals and learners wanting to create interactive analytics tools, dashboards, or data-driven web applications.

Make the most of your data using the power of Excel When you think of data, do you think of endless rows and columns in spreadsheets? Excel Dashboards and Reports For Dummies, 3 shows you how to make the most of your data—and puts an end to mind-numbing spreadsheets by exploring new ways to conceptualize and present key information. There's often a gap between handling data and synthesizing it into meaningful reports, and this approachable text bridges this gap with quick and accessible information that answers key questions, like how to meaningfully capture data trends, how to show relationships in data, and when it's better to show variances than actual data values. rd Edition As a leading spreadsheet application, Microsoft Excel is the go-to data software. This tool allows you to use dashboard reports that leverage gauges, maps, charts, sliders, and other visual elements to present complex data in a manner that's easy to understand. Using Excel dashboards effectively can improve your professional capabilities by leaps and bounds. Analyze and report on large amounts of data in a meaningful way Look at data from different perspectives, and better visualize the information you're presenting by quickly slicing data on the fly Automate redundant reporting and analysis functions, making your data analysis and reporting routine more efficient Create visualizations, dashboards, and what-if analyses that are as visually appealing as they are substantial Excel Dashboards and Reports For Dummies, 3 is a fantastic resource if you're looking to spice up your reporting! rd Edition

Transform your organization's data into actionable insights with Tableau Tableau is designed specifically to provide fast and easy visual analytics. The intuitive drag-and-drop interface helps you create interactive reports, dashboards, and visualizations, all without any special or advanced training. This all new edition of Tableau Your Data! is your Tableau companion, helping you get the most out of this invaluable business toolset. Tableau Your Data! shows you how to build dynamic, best of breed visualizations using the Tableau Software toolset. This comprehensive guide covers the core feature set for data analytics, and provides clear step-by-step guidance toward best practices and advanced techniques that go way beyond the user manual. You'll learn how Tableau is different from traditional business information analysis tools, and how to navigate your way around the Tableau 9.0 desktop before delving into functions and calculations, as well as sharing with the Tableau Server. Analyze data more effectively with Tableau Desktop Customize Tableau's settings for your organization's needs with detailed real-world examples on data security, scaling, syntax, and more Deploy visualizations to consumers throughout the enterprise - from sales to marketing, operations to finance, and beyond Understand Tableau functions and calculations and leverage Tableau across every link in the value chain Learn from actual working models of the book's visualizations and other web-based resources via a companion website Tableau helps you unlock the stories within the numbers, and Tableau Your Data! puts the software's full functionality right at your fingertips.

This book illustrates the application of perfect simulation ideas and algorithms to a wide range of problems. The author describes numerous protocol methodologies for designing algorithms for specific problems. He first examines the commonly used acceptance/rejection (AR) protocol for creating perfect simulation algorithms. He then covers other major protocols, including coupling from the past (CFTP); the Fill, Machida, Murdoch, and Rosenthal (FMMR) method; the randomness recycler; retrospective sampling; and partially recursive AR, along with multiple variants of these protocols.

Fundamentals of Big Data Network Analysis for Research and Industry Hyunjoung Lee, Institute of Green Technology, Yonsei University, Republic of Korea Il Sohn, Material Science and Engineering, Yonsei University, Republic of Korea Presents the methodology of big data analysis using examples from research and industry There are large amounts of data everywhere, and the ability to pick out crucial information is increasingly important. Contrary to popular belief, not all information is useful; big data network analysis assumes that data is not only large, but also meaningful, and this book focuses on the fundamental techniques required to extract essential information from vast datasets. Featuring case studies drawn largely from the iron and steel industries, this book offers practical guidance which will enable readers to easily understand big data network analysis. Particular attention is paid to the methodology of network analysis, offering information on the method of data collection, on research design and analysis, and on the interpretation of results. A variety of programs including UCINET, NetMiner, R, NodeXL, and Gephi for network analysis are covered in detail. Fundamentals of Big Data Network Analysis for Research and Industry looks at big data from a fresh perspective, and provides a new approach to data analysis. This book: Explains the basic concepts in understanding big data and filtering meaningful data Presents big data analysis within the networking perspective Features methodology applicable to research and industry Describes in detail the social relationship between big data and its implications Provides insight into identifying patterns and relationships between seemingly unrelated big data Fundamentals of Big Data Network Analysis for Research and Industry will prove a valuable resource for analysts, research engineers, industrial engineers, marketing professionals, and any individuals dealing with accumulated large data whose interest is to analyze and identify potential relationships among data sets.

This book is about the concept of “Quality of Life”. What is necessary for quality of life, and how can it be measured? The approach is a multicriterial scheme reduction which prevents as much information loss as possible when shifting from the set of partial criteria to their convolution. This book is written for researchers, analysts and graduate and postgraduate students of mathematics and economics.

The apparent contradiction between statistical significance and biological relevance has diminished the value of statistical methods as a whole in toxicology. Moreover, recommendations for statistical analysis are imprecise in most toxicological guidelines. Addressing these dilemmas, Statistics in Toxicology Using R explains the statistical analysis of selected experimental data in toxicology and presents assay-specific suggestions, such as for the in vitro micronucleus assay. Mostly focusing on hypothesis testing, the book covers standardized bioassays for chemicals, drugs, and environmental pollutants. It is organized according to selected toxicological assays, including:Short-term repeated toxicity studiesLong-term carcinogenicity assaysStudies on reproductive toxicityMutagenicity assaysToxicokinetic studiesThe book also discusses proof of safety (particularly in ecotoxicological assays), toxicogenomics, the analysis of interlaboratory studies and the modeling of dose-response relationships for risk assessment. For each toxicological problem, the author describes the statistics involved, matching data example, R code, and outcomes and their interpretation. This approach allows you to select a certain bioassay, identify the specific data structure, run the R code with the data example, understand the test outcome and interpretation, and replace the data set with your own data and run again.Supporting material for this title can be downloaded here.