Download or read book Visualization Analysis and Design written by Tamara Munzner and published by CRC Press. This book was released on 2014-12-01 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn How to Design Effective Visualization SystemsVisualization Analysis and Design provides a systematic, comprehensive framework for thinking about visualization in terms of principles and design choices. The book features a unified approach encompassing information visualization techniques for abstract data, scientific visualization techniques

Download or read book A Step by Step Guide to Exploratory Factor Analysis with Stata written by Marley Watkins and published by Taylor & Francis. This book was released on 2021-09-08 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a concise, easy to use, step-by-step guide for applied researchers conducting exploratory factor analysis (EFA) using Stata. In this book, Dr. Watkins systematically reviews each decision step in EFA with screen shots of Stata code and recommends evidence-based best practice procedures. This is an eminently applied, practical approach with few or no formulas and is aimed at readers with little to no mathematical background. Dr. Watkins maintains an accessible tone throughout and uses minimal jargon and formula to help facilitate grasp of the key issues users will face when applying EFA, along with how to implement, interpret, and report results. Copious scholarly references and quotations are included to support the reader in responding to editorial reviews. This is a valuable resource for upper level undergraduate and postgraduate students, as well as for more experienced researchers undertaking multivariate or structure equation modeling courses across the behavioral, medical, and social sciences.

Download or read book Measuring Culture written by John W. Mohr and published by Columbia University Press. This book was released on 2020-08-11 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social scientists seek to develop systematic ways to understand how people make meaning and how the meanings they make shape them and the world in which they live. But how do we measure such processes? Measuring Culture is an essential point of entry for both those new to the field and those who are deeply immersed in the measurement of meaning. Written collectively by a team of leading qualitative and quantitative sociologists of culture, the book considers three common subjects of measurement—people, objects, and relationships—and then discusses how to pivot effectively between subjects and methods. Measuring Culture takes the reader on a tour of the state of the art in measuring meaning, from discussions of neuroscience to computational social science. It provides both the definitive introduction to the sociological literature on culture as well as a critical set of case studies for methods courses across the social sciences.

Download or read book Statistics Using SPSS written by Sharon Lawner Weinberg and published by Cambridge University Press. This book was released on 2008-03-03 with total page 13 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied statistics text updated to be consistent with SPSS version 15, ideal for classroom use or self study.

Download or read book Exploratory Data Analysis with MATLAB written by Wendy L. Martinez and published by CRC Press. This book was released on 2017-08-07 with total page 590 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the Second Edition: "The authors present an intuitive and easy-to-read book. ... accompanied by many examples, proposed exercises, good references, and comprehensive appendices that initiate the reader unfamiliar with MATLAB." —Adolfo Alvarez Pinto, International Statistical Review "Practitioners of EDA who use MATLAB will want a copy of this book. ... The authors have done a great service by bringing together so many EDA routines, but their main accomplishment in this dynamic text is providing the understanding and tools to do EDA. —David A Huckaby, MAA Reviews Exploratory Data Analysis (EDA) is an important part of the data analysis process. The methods presented in this text are ones that should be in the toolkit of every data scientist. As computational sophistication has increased and data sets have grown in size and complexity, EDA has become an even more important process for visualizing and summarizing data before making assumptions to generate hypotheses and models. Exploratory Data Analysis with MATLAB, Third Edition presents EDA methods from a computational perspective and uses numerous examples and applications to show how the methods are used in practice. The authors use MATLAB code, pseudo-code, and algorithm descriptions to illustrate the concepts. The MATLAB code for examples, data sets, and the EDA Toolbox are available for download on the book’s website. New to the Third Edition Random projections and estimating local intrinsic dimensionality Deep learning autoencoders and stochastic neighbor embedding Minimum spanning tree and additional cluster validity indices Kernel density estimation Plots for visualizing data distributions, such as beanplots and violin plots A chapter on visualizing categorical data

Download or read book R Visualizations written by David Gerbing and published by CRC Press. This book was released on 2020-04-28 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: R Visualizations: Derive Meaning from Data focuses on one of the two major topics of data analytics: data visualization, a.k.a., computer graphics. In the book, major R systems for visualization are discussed, organized by topic and not by system. Anyone doing data analysis will be shown how to use R to generate any of the basic visualizations with the R visualization systems. Further, this book introduces the author’s lessR system, which always can accomplish a visualization with less coding than the use of other systems, sometimes dramatically so, and also provides accompanying statistical analyses. Key Features Presents thorough coverage of the leading R visualization system, ggplot2. Gives specific guidance on using base R graphics to attain visualizations of the same quality as those provided by ggplot2. Shows how to create a wide range of data visualizations: distributions of categorical and continuous variables, many types of scatterplots including with a third variable, time series, and maps. Inclusion of the various approaches to R graphics organized by topic instead of by system. Presents the recent work on interactive visualization in R. David W. Gerbing received his PhD from Michigan State University in 1979 in quantitative analysis, and currently is a professor of quantitative analysis in the School of Business at Portland State University. He has published extensively in the social and behavioral sciences with a focus on quantitative methods. His lessR package has been in development since 2009.

Download or read book A Step by Step Guide to Exploratory Factor Analysis with SPSS written by Marley W. Watkins and published by Routledge. This book was released on 2021-06-21 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a concise, easy to use, step-by-step guide for applied researchers conducting exploratory factor analysis (EFA) using SPSS. In this book, Dr. Watkins systematically reviews each decision step in EFA with screen shots and code from SPSS and recommends evidence-based best-practice procedures. This is an eminently applied, practical approach with few or no formulas and is aimed at readers with little to no mathematical background. Dr. Watkins maintains an accessible tone throughout and uses minimal jargon to help facilitate grasp of the key issues users will face while applying EFA, along with how to implement, interpret, and report results. Copious scholarly references and quotations are included to support the reader in responding to editorial reviews. This is a valuable resource for upper-level undergraduate and postgraduate students, as well as for more experienced researchers undertaking multivariate or structure equation modeling courses across the behavioral, medical, and social sciences.

Download or read book R Data Mining written by Andrea Cirillo and published by Packt Publishing Ltd. This book was released on 2017-11-29 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mine valuable insights from your data using popular tools and techniques in R About This Book Understand the basics of data mining and why R is a perfect tool for it. Manipulate your data using popular R packages such as ggplot2, dplyr, and so on to gather valuable business insights from it. Apply effective data mining models to perform regression and classification tasks. Who This Book Is For If you are a budding data scientist, or a data analyst with a basic knowledge of R, and want to get into the intricacies of data mining in a practical manner, this is the book for you. No previous experience of data mining is required. What You Will Learn Master relevant packages such as dplyr, ggplot2 and so on for data mining Learn how to effectively organize a data mining project through the CRISP-DM methodology Implement data cleaning and validation tasks to get your data ready for data mining activities Execute Exploratory Data Analysis both the numerical and the graphical way Develop simple and multiple regression models along with logistic regression Apply basic ensemble learning techniques to join together results from different data mining models Perform text mining analysis from unstructured pdf files and textual data Produce reports to effectively communicate objectives, methods, and insights of your analyses In Detail R is widely used to leverage data mining techniques across many different industries, including finance, medicine, scientific research, and more. This book will empower you to produce and present impressive analyses from data, by selecting and implementing the appropriate data mining techniques in R. It will let you gain these powerful skills while immersing in a one of a kind data mining crime case, where you will be requested to help resolving a real fraud case affecting a commercial company, by the mean of both basic and advanced data mining techniques. While moving along the plot of the story you will effectively learn and practice on real data the various R packages commonly employed for this kind of tasks. You will also get the chance of apply some of the most popular and effective data mining models and algos, from the basic multiple linear regression to the most advanced Support Vector Machines. Unlike other data mining learning instruments, this book will effectively expose you the theory behind these models, their relevant assumptions and when they can be applied to the data you are facing. By the end of the book you will hold a new and powerful toolbox of instruments, exactly knowing when and how to employ each of them to solve your data mining problems and get the most out of your data. Finally, to let you maximize the exposure to the concepts described and the learning process, the book comes packed with a reproducible bundle of commented R scripts and a practical set of data mining models cheat sheets. Style and approach This book takes a practical, step-by-step approach to explain the concepts of data mining. Practical use-cases involving real-world datasets are used throughout the book to clearly explain theoretical concepts.

Download or read book Python for Data Science For Dummies written by John Paul Mueller and published by John Wiley & Sons. This book was released on 2023-10-03 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: Let Python do the heavy lifting for you as you analyze large datasets Python for Data Science For Dummies lets you get your hands dirty with data using one of the top programming languages. This beginner’s guide takes you step by step through getting started, performing data analysis, understanding datasets and example code, working with Google Colab, sampling data, and beyond. Coding your data analysis tasks will make your life easier, make you more in-demand as an employee, and open the door to valuable knowledge and insights. This new edition is updated for the latest version of Python and includes current, relevant data examples. Get a firm background in the basics of Python coding for data analysis Learn about data science careers you can pursue with Python coding skills Integrate data analysis with multimedia and graphics Manage and organize data with cloud-based relational databases Python careers are on the rise. Grab this user-friendly Dummies guide and gain the programming skills you need to become a data pro.

Download or read book Introduction to Statistical Methods for Biosurveillance written by Ronald D. Fricker and published by Cambridge University Press. This book was released on 2013-02-25 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bioterrorism is not a new threat, but in an increasingly interconnected world, the potential for catastrophic outcomes is greater today than ever. The medical and public health communities are establishing biosurveillance systems designed to proactively monitor populations for possible disease outbreaks as a first line of defense. The ideal biosurveillance system should identify trends not visible to individual physicians and clinicians in near-real time. Many of these systems use statistical algorithms to look for anomalies and to trigger epidemiologic investigation, quantification, localization and outbreak management. This book discusses the design and evaluation of statistical methods for effective biosurveillance for readers with minimal statistical training. Weaving public health and statistics together, it presents basic and more advanced methods, with a focus on empirically demonstrating added value. Although the emphasis is on epidemiologic and syndromic surveillance, the statistical methods can be applied to a broad class of public health surveillance problems.

Download or read book Beginning JavaScript Charts written by Fabio Nelli and published by Apress. This book was released on 2014-01-24 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: Beginning JavaScript Charts shows how to convert your data into eye-catching, innovative, animated, and highly interactive browser-based charts. This book is suitable for developers of all experience levels and needs: for those who love fast and effective solutions, you can use the jqPlot library to generate charts with amazing effects and animations using only a few lines of code; if you want more power and need to create data visualization beyond traditional charts, then D3 is the JavaScript library for you; finally, if you need a high-performance, professional solution for interactive charts, then the Highcharts library is also covered. If you are an experienced developer and want to take things further, then Beginning JavaScript Charts also shows you how to develop your own graphics library starting from scratch using jQuery. At the end of the book, you will have a good knowledge of all the elements needed to manage data from every possible source, from high-end scientific instruments to Arduino boards, from PHP SQL databases queries to simple HTML tables, and from Matlab calculations to reports in Excel. You will be able to provide cutting-edge charts exploiting the growing power of modern browsers. Create all kinds of charts using the latest technologies available on browsers (HTML5, CSS3, jQuery, jqPlot, D3, Highcharts, and SVG) Full of step-by-step examples, Beginning JavaScript Charts introduces you gradually to all aspects of chart development, from the data source to the choice of which solution to apply. This book provides a number of tools that can be the starting point for any project requiring graphical representations of data, whether using commercial libraries or your own

Download or read book Information Systems and Neuroscience written by Fred D. Davis and published by Springer Nature. This book was released on 2021-10-28 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the NeuroIS Retreat 2021, June 1-3, virtual conference, reporting on topics at the intersection of information systems (IS) research, neurophysiology and the brain sciences. Readers will discover the latest findings from top scholars in the field of NeuroIS, which offer detailed insights on the neurobiology underlying IS behavior, essential methods and tools and their applications for IS, as well as the application of neuroscience and neurophysiological theories to advance IS theory.

Download or read book Essential Fish Habitat Designation and Minimization of Adverse Impacts Pacific Coast Groundfish Fishery Management Plan written by and published by . This book was released on 2005 with total page 670 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Excel 2010 for Environmental Sciences Statistics written by Thomas J. Quirk and published by Springer. This book was released on 2015-11-29 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book to show the capabilities of Microsoft Excel to teach environmental sciences statistics effectively. It is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical environmental sciences problems. If understanding statistics isn’t your strongest suit, you are not especially mathematically-inclined, or if you are wary of computers, this is the right book for you. Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in environmental science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2010 for Environmental Sciences Statistics: A Guide to Solving Practical Problems is the first book to capitalize on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work. Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand environmental science problems. Practice problems are provided at the end of each chapter with their solutions in an appendix. Separately, there is a full Practice Test (with answers in an Appendix) that allows readers to test what they have learned.

Download or read book SPSS Data Analysis for Univariate Bivariate and Multivariate Statistics written by Daniel J. Denis and published by John Wiley & Sons. This book was released on 2018-09-25 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Enables readers to start doing actual data analysis fast for a truly hands-on learning experience This concise and very easy-to-use primer introduces readers to a host of computational tools useful for making sense out of data, whether that data come from the social, behavioral, or natural sciences. The book places great emphasis on both data analysis and drawing conclusions from empirical observations. It also provides formulas where needed in many places, while always remaining focused on concepts rather than mathematical abstraction. SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics offers a variety of popular statistical analyses and data management tasks using SPSS that readers can immediately apply as needed for their own research, and emphasizes many helpful computational tools used in the discovery of empirical patterns. The book begins with a review of essential statistical principles before introducing readers to SPSS. The book then goes on to offer chapters on: Exploratory Data Analysis, Basic Statistics, and Visual Displays; Data Management in SPSS; Inferential Tests on Correlations, Counts, and Means; Power Analysis and Estimating Sample Size; Analysis of Variance – Fixed and Random Effects; Repeated Measures ANOVA; Simple and Multiple Linear Regression; Logistic Regression; Multivariate Analysis of Variance (MANOVA) and Discriminant Analysis; Principal Components Analysis; Exploratory Factor Analysis; and Non-Parametric Tests. This helpful resource allows readers to: Understand data analysis in practice rather than delving too deeply into abstract mathematical concepts Make use of computational tools used by data analysis professionals. Focus on real-world application to apply concepts from the book to actual research Assuming only minimal, prior knowledge of statistics, SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics is an excellent “how-to” book for undergraduate and graduate students alike. This book is also a welcome resource for researchers and professionals who require a quick, go-to source for performing essential statistical analyses and data management tasks.

Download or read book Storytelling with Data written by Cole Nussbaumer Knaflic and published by John Wiley & Sons. This book was released on 2015-10-09 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it!

Download or read book Statistical Applications for Environmental Analysis and Risk Assessment written by Joseph Ofungwu and published by John Wiley & Sons. This book was released on 2014-05-06 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Applications for Environmental Analysis and Risk Assessment guides readers through real-world situations and the best statistical methods used to determine the nature and extent of the problem, evaluate the potential human health and ecological risks, and design and implement remedial systems as necessary. Featuring numerous worked examples using actual data and “ready-made” software scripts, Statistical Applications for Environmental Analysis and Risk Assessment also includes: • Descriptions of basic statistical concepts and principles in an informal style that does not presume prior familiarity with the subject • Detailed illustrations of statistical applications in the environmental and related water resources fields using real-world data in the contexts that would typically be encountered by practitioners • Software scripts using the high-powered statistical software system, R, and supplemented by USEPA’s ProUCL and USDOE’s VSP software packages, which are all freely available • Coverage of frequent data sample issues such as non-detects, outliers, skewness, sustained and cyclical trend that habitually plague environmental data samples • Clear demonstrations of the crucial, but often overlooked, role of statistics in environmental sampling design and subsequent exposure risk assessment.