The Visual Display Of Quantitative Data Pdf
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📒Applications Of Data Centric Science To Social Design ✍ Aki-Hiro Sato
✏Applications of Data Centric Science to Social Design Book Summary : The intention behind this book is to illustrate the deep relation among human behavior, data-centric science, and social design. In fact, these three issues have been independently developing in different fields, although they are, of course, deeply interrelated to one another. Specifically, fundamental understanding of human behavior should be employed for investigating our human society and designing social systems. Insights and both quantitative and qualitative understandings of collective human behavior are quite useful when social systems are designed. Fundamental principles of human behavior, theoretical models of human behavior, and information cascades are addressed as aspects of human behavior. Data-driven investigation of human nature, social behavior, and societal systems are developed as aspects of data-centric science. As design aspects, how to design social systems from heterogeneous memberships is explained. There is also discussion of these three aspects—human behavior, data-centric science, and social design—independently and with regard to the relationships among them.
📒Innovative Approaches Of Data Visualization And Visual Analytics ✍ Huang, Mao Lin
✏Innovative Approaches of Data Visualization and Visual Analytics Book Summary : Due to rapid advances in hardware and software technologies, network infrastructure and data have become increasingly complex, requiring efforts to more effectively comprehend and analyze network topologies and information systems. Innovative Approaches of Data Visualization and Visual Analytics evaluates the latest trends and developments in force-based data visualization techniques, addressing issues in the design, development, evaluation, and application of algorithms and network topologies. This book will assist professionals and researchers working in the fields of data analysis and information science, as well as students in computer science and computer engineering, in developing increasingly effective methods of knowledge creation, management, and preservation.
📒Web And Network Data Science ✍ Thomas W. Miller
✏Web and Network Data Science Book Summary : Master modern web and network data modeling: both theory and applications. In Web and Network Data Science, a top faculty member of Northwestern University’s prestigious analytics program presents the first fully-integrated treatment of both the business and academic elements of web and network modeling for predictive analytics. Some books in this field focus either entirely on business issues (e.g., Google Analytics and SEO); others are strictly academic (covering topics such as sociology, complexity theory, ecology, applied physics, and economics). This text gives today's managers and students what they really need: integrated coverage of concepts, principles, and theory in the context of real-world applications. Building on his pioneering Web Analytics course at Northwestern University, Thomas W. Miller covers usability testing, Web site performance, usage analysis, social media platforms, search engine optimization (SEO), and many other topics. He balances this practical coverage with accessible and up-to-date introductions to both social network analysis and network science, demonstrating how these disciplines can be used to solve real business problems.
📒Handbook Of Quantitative Criminology ✍ Alex R. Piquero
✏Handbook of Quantitative Criminology Book Summary : Quantitative criminology has certainly come a long way since I was ?rst introduced to a largely qualitative criminology some 40 years ago, when I was recruited to lead a task force on science and technology for the President’s Commission on Law Enforcement and Administration of Justice. At that time, criminology was a very limited activity, depending almost exclusively on the Uniform Crime Reports (UCR) initiated by the FBI in 1929 for measurement of crime based on victim reports to the police and on police arrests. A ty- cal mode of analysis was simple bivariate correlation. Marvin Wolfgang and colleagues were makingan importantadvancebytrackinglongitudinaldata onarrestsin Philadelphia,an in- vation that was widely appreciated. And the ?eld was very small: I remember attending my ?rst meeting of the American Society of Criminology in about 1968 in an anteroom at New York University; there were about 25–30 people in attendance, mostly sociologists with a few lawyers thrown in. That Society today has over 3,000 members, mostly now drawn from criminology which has established its own clear identity, but augmented by a wide variety of disciplines that include statisticians, economists, demographers, and even a few engineers. This Handbook provides a remarkable testimony to the growth of that ?eld. Following the maxim that “if you can’t measure it, you can’t understand it,” we have seen the early dissatisfaction with the UCR replaced by a wide variety of new approaches to measuring crime victimization and offending.
📒Spatial Data Analysis In Ecology And Agriculture Using R Second Edition ✍ Richard E. Plant
✏Spatial Data Analysis in Ecology and Agriculture Using R Second Edition Book Summary : Key features: Unique in its combination of serving as an introduction to spatial statistics and to modeling agricultural and ecological data using R Provides exercises in each chapter to facilitate the book's use as a course textbook or for self-study Adds new material on generalized additive models, point pattern analysis, and new methods of Bayesian analysis of spatial data. Includes a completely revised chapter on the analysis of spatiotemporal data featuring recently introduced software and methods Updates its coverage of R software including newly introduced packages Spatial Data Analysis in Ecology and Agriculture Using R, 2nd Edition provides practical instruction on the use of the R programming language to analyze spatial data arising from research in ecology, agriculture, and environmental science. Readers have praised the book's practical coverage of spatial statistics, real-world examples, and user-friendly approach in presenting and explaining R code, aspects maintained in this update. Using data sets from cultivated and uncultivated ecosystems, the book guides the reader through the analysis of each data set, including setting research objectives, designing the sampling plan, data quality control, exploratory and confirmatory data analysis, and drawing scientific conclusions. Additional material to accompany the book, on both analyzing satellite data and on multivariate analysis, can be accessed at https://www.plantsciences.ucdavis.edu/plant/additionaltopics.htm.
📒Developing Quantitative Literacy Skills In History And The Social Sciences ✍ Kathleen W. Craver
✏Developing Quantitative Literacy Skills in History and the Social Sciences Book Summary : This book features 85 interesting and exciting multi-century and multicultural web sites that are accompanied by numerical critical thinking questions and activities. Teachers can pose the questions to their entire class or individually assign them. It also contains lists of best practices and examples for interpreting, visualizing, and displaying quantitative data. History and social sciences educators will find this book an indispensable tool for incorporating numerical literacy skills into their class activities and assignments.
📒Visual Explanations ✍ Edward R. Tufte
✏Visual Explanations Book Summary : Display of information for paper and computer screens; principles of information design, design of presentations. Depicting evidence relevant to cause and effect, decision making. Scientific visualization.
📒Global Climate Change ✍ Arnold Jeffrey Bloom
✏Global Climate Change Book Summary : Mark Twain's comment that everybody talks about the weather, but nobody does anything about it no longer applies: human activities have altered the global climate, and governments are having to act now to avoid more extreme perturbations. Global Climate Change examines the factors responsible for global climate change and the geophysical, biological, economic, legal, and cultural consequences of such changes. The book highlights the complexity of decision-making under uncertainty, contrasting the methods that various disciplines employ to evaluate past and future conditions
📒Modeling Techniques In Predictive Analytics With Python And R ✍ Thomas W. Miller
✏Modeling Techniques in Predictive Analytics with Python and R Book Summary : Master predictive analytics, from start to finish Start with strategy and management Master methods and build models Transform your models into highly-effective code—in both Python and R This one-of-a-kind book will help you use predictive analytics, Python, and R to solve real business problems and drive real competitive advantage. You’ll master predictive analytics through realistic case studies, intuitive data visualizations, and up-to-date code for both Python and R—not complex math. Step by step, you’ll walk through defining problems, identifying data, crafting and optimizing models, writing effective Python and R code, interpreting results, and more. Each chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work—and maximize their value. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, addresses everything you need to succeed: strategy and management, methods and models, and technology and code. If you’re new to predictive analytics, you’ll gain a strong foundation for achieving accurate, actionable results. If you’re already working in the field, you’ll master powerful new skills. If you’re familiar with either Python or R, you’ll discover how these languages complement each other, enabling you to do even more. All data sets, extensive Python and R code, and additional examples available for download at http://www.ftpress.com/miller/ Python and R offer immense power in predictive analytics, data science, and big data. This book will help you leverage that power to solve real business problems, and drive real competitive advantage. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, illuminating each technique with carefully explained code for the latest versions of Python and R. If you’re new to predictive analytics, Miller gives you a strong foundation for achieving accurate, actionable results. If you’re already a modeler, programmer, or manager, you’ll learn crucial skills you don’t already have. Using Python and R, Miller addresses multiple business challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic code that delivers actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. Appendices include five complete case studies, and a detailed primer on modern data science methods. Use Python and R to gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more
📒Encyclopedia Of Measurement And Statistics ✍ Neil J. Salkind
✏Encyclopedia of Measurement and Statistics Book Summary : The Encyclopedia of Measurement and Statistics presents state-of-the-art information and ready-to-use facts from the fields of measurement and statistics in an unintimidating style. The ideas and tools contained in these pages are approachable and can be invaluable for understanding our very technical world and the increasing flow of information. Although there are references that cover statistics and assessment in depth, none provides as comprehensive a resource in as focused and accessible a manner as the three volumes of this Encyclopedia. Through approximately 500 contributions, experts provide an overview and an explanation of the major topics in these two areas.