Making Sense of Data I

A Practical Guide to Exploratory Data Analysis and Data Mining
Author: Glenn J. Myatt,Wayne P. Johnson
Publisher: John Wiley & Sons
ISBN: 1118422104
Category: Mathematics
Page: 248
View: 1320

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Praise for the First Edition “...a well-written book on data analysis and data mining that provides an excellent foundation...” —CHOICE “This is a must-read book for learning practical statistics and data analysis...” —Computing Reviews.com A proven go-to guide for data analysis, Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second Edition focuses on basic data analysis approaches that are necessary to make timely and accurate decisions in a diverse range of projects. Based on the authors’ practical experience in implementing data analysis and data mining, the new edition provides clear explanations that guide readers from almost every field of study. In order to facilitate the needed steps when handling a data analysis or data mining project, a step-by-step approach aids professionals in carefully analyzing data and implementing results, leading to the development of smarter business decisions. The tools to summarize and interpret data in order to master data analysis are integrated throughout, and the Second Edition also features: Updated exercises for both manual and computer-aided implementation with accompanying worked examples New appendices with coverage on the freely available Traceis™ software, including tutorials using data from a variety of disciplines such as the social sciences, engineering, and finance New topical coverage on multiple linear regression and logistic regression to provide a range of widely used and transparent approaches Additional real-world examples of data preparation to establish a practical background for making decisions from data Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second Edition is an excellent reference for researchers and professionals who need to achieve effective decision making from data. The Second Edition is also an ideal textbook for undergraduate and graduate-level courses in data analysis and data mining and is appropriate for cross-disciplinary courses found within computer science and engineering departments.

Making Sense of Data III

A Practical Guide to Designing Interactive Data Visualizations
Author: Glenn J. Myatt,Wayne P. Johnson
Publisher: John Wiley & Sons
ISBN: 1118121600
Category: Mathematics
Page: 416
View: 4962

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Focuses on insights, approaches, and techniques that are essential to designing interactive graphics and visualizations Making Sense of Data III: A Practical Guide to Designing Interactive Data Visualizations explores a diverse range of disciplines to explain how meaning from graphical representations is extracted. Additionally, the book describes the best approach for designing and implementing interactive graphics and visualizations that play a central role in data exploration and decision-support systems. Beginning with an introduction to visual perception, Making Sense of Data III features a brief history on the use of visualization in data exploration and an outline of the design process. Subsequent chapters explore the following key areas: Cognitive and Visual Systems describes how various drawings, maps, and diagrams known as external representations are understood and used to extend the mind's capabilities Graphics Representations introduces semiotic theory and discusses the seminal work of cartographer Jacques Bertin and the grammar of graphics as developed by Leland Wilkinson Designing Visual Interactions discusses the four stages of design process—analysis, design, prototyping, and evaluation—and covers the important principles and strategies for designing visual interfaces, information visualizations, and data graphics Hands-on: Creative Interactive Visualizations with Protovis provides an in-depth explanation of the capabilities of the Protovis toolkit and leads readers through the creation of a series of visualizations and graphics The final chapter includes step-by-step examples that illustrate the implementation of the discussed methods, and a series of exercises are provided to assist in learning the Protovis language. A related website features the source code for the presented software as well as examples and solutions for select exercises. Featuring research in psychology, vision science, statistics, and interaction design, Making Sense of Data III is an indispensable book for courses on data analysis and data mining at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for computational statisticians, software engineers, researchers, and professionals of any discipline who would like to understand how the mind processes graphical representations.

Making Sense of Data II

A Practical Guide to Data Visualization, Advanced Data Mining Methods, and Applications
Author: Glenn J. Myatt,Wayne P. Johnson
Publisher: John Wiley & Sons
ISBN: 9780470417393
Category: Mathematics
Page: 416
View: 6248

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A hands-on guide to making valuable decisions from data using advanced data mining methods and techniques This second installment in the Making Sense of Data series continues to explore a diverse range of commonly used approaches to making and communicating decisions from data. Delving into more technical topics, this book equips readers with advanced data mining methods that are needed to successfully translate raw data into smart decisions across various fields of research including business, engineering, finance, and the social sciences. Following a comprehensive introduction that details how to define a problem, perform an analysis, and deploy the results, Making Sense of Data II addresses the following key techniques for advanced data analysis: Data Visualization reviews principles and methods for understanding and communicating data through the use of visualization including single variables, the relationship between two or more variables, groupings in data, and dynamic approaches to interacting with data through graphical user interfaces. Clustering outlines common approaches to clustering data sets and provides detailed explanations of methods for determining the distance between observations and procedures for clustering observations. Agglomerative hierarchical clustering, partitioned-based clustering, and fuzzy clustering are also discussed. Predictive Analytics presents a discussion on how to build and assess models, along with a series of predictive analytics that can be used in a variety of situations including principal component analysis, multiple linear regression, discriminate analysis, logistic regression, and Naïve Bayes. Applications demonstrates the current uses of data mining across a wide range of industries and features case studies that illustrate the related applications in real-world scenarios. Each method is discussed within the context of a data mining process including defining the problem and deploying the results, and readers are provided with guidance on when and how each method should be used. The related Web site for the series (www.makingsenseofdata.com) provides a hands-on data analysis and data mining experience. Readers wishing to gain more practical experience will benefit from the tutorial section of the book in conjunction with the TraceisTM software, which is freely available online. With its comprehensive collection of advanced data mining methods coupled with tutorials for applications in a range of fields, Making Sense of Data II is an indispensable book for courses on data analysis and data mining at the upper-undergraduate and graduate levels. It also serves as a valuable reference for researchers and professionals who are interested in learning how to accomplish effective decision making from data and understanding if data analysis and data mining methods could help their organization.

Making Sense of Data Set


Author: Glenn J. Myatt
Publisher: Wiley
ISBN: 9781118395141
Category: Mathematics
Page: 991
View: 5462

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Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining by Glenn J. Myatt (978-0-470-07471-8), Making Sense of Data II: A Practical Guide to Data Visualization, Advanced Data Mining Methods, and Applications by Glenn J. Myatt and Wayne P. Johnson (978-0-470-22280-5), and Making Sense of Data III: A Practical Guide to Designing Interactive Data Visualizations by Glenn J. Myatt and Wayne P. Johnson (978-0-470-53649-0)

Machine Learning

The Art and Science of Algorithms that Make Sense of Data
Author: Peter Flach
Publisher: Cambridge University Press
ISBN: 1107096391
Category: Computers
Page: 396
View: 2505

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Covering all the main approaches in state-of-the-art machine learning research, this will set a new standard as an introductory textbook.

Making Sense of Men

A Woman's Guide a Lifetime of Love, Care and Attention from All Men
Author: Alison A. Armstrong
Publisher: Pax Pub
ISBN: 9781605309095
Category: Family & Relationships
Page: 73
View: 4024

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Step into the world of Alison Armstrong, where love, care, and attention from men are normal and relied upon-and a way of life available for every women. Do you have to sell our soul? Not even close. This book can be your guide, an unexpected friend, even a prophecy for your future. Funny information-packed text, illustrative charts and enlightening side-bars will deliver priceless insights into men their motivations and their inspirations. Making Sense of Men will teach you:"Why men pursue some women for sex and others for heart-felt relationships"How to tell when a man is emotionally involved"How to inspire generosity and attentiveness in all men"How you can be strong and successful-without discouraging men

Making Sense of Intractable Environmental Conflicts

Concepts and Cases
Author: Roy Lewicki
Publisher: Island Press
ISBN: 161091287X
Category: Nature
Page: 296
View: 3853

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Despite a vast amount of effort and expertise devoted to them, many environmental conflicts have remained mired in controversy, stubbornly defying resolution. Why can some environmental problems be resolved in one locale but remain contentious in another, often carrying on for decades? What is it about certain issues or the people involved that make a conflict seemingly insoluble? Making Sense of Intractable Environmental Conflicts addresses those and related questions, examining what researchers and experts in the field characterize as "intractable" disputes—intense disputes that persist over long periods of time and cannot be resolved through consensus-building efforts or by administrative, legal, or political means. The approach focuses on the "frames" parties use to define and enact the dispute—the lenses through which they interpret and understand the conflict and critical conflict dynamics. Through analysis of interviews, news media coverage, meeting transcripts, and archival data, the contributors to the book examine the concept of framing and the role that it plays in conflicts; outline the essential characteristics of intractability and its major causes; offer case studies of eight intractable environmental conflicts; present a rich body of original interview material from affected parties; and set forth recommendations for intervention that can help resolve disputes. Within each case chapter, the authors describe the historical development and fundamental nature of the conflict and then analyze the case from the perspective of the key frames that are integral to understanding the dynamics of the dispute. They also offer cross-case analyses of related conflicts. Conflicts examined include those over natural resource use, toxic pollutants, water quality, and growth.

Getting Started with Data Science

Making Sense of Data with Analytics
Author: Murtaza Haider
Publisher: IBM Press
ISBN: 0133991237
Category: Business & Economics
Page: 400
View: 343

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Master Data Analytics Hands-On by Solving Fascinating Problems You’ll Actually Enjoy! Harvard Business Review recently called data science “The Sexiest Job of the 21st Century.” It’s not just sexy: For millions of managers, analysts, and students who need to solve real business problems, it’s indispensable. Unfortunately, there’s been nothing easy about learning data science–until now. Getting Started with Data Science takes its inspiration from worldwide best-sellers like Freakonomics and Malcolm Gladwell’s Outliers: It teaches through a powerful narrative packed with unforgettable stories. Murtaza Haider offers informative, jargon-free coverage of basic theory and technique, backed with plenty of vivid examples and hands-on practice opportunities. Everything’s software and platform agnostic, so you can learn data science whether you work with R, Stata, SPSS, or SAS. Best of all, Haider teaches a crucial skillset most data science books ignore: how to tell powerful stories using graphics and tables. Every chapter is built around real research challenges, so you’ll always know why you’re doing what you’re doing. You’ll master data science by answering fascinating questions, such as: • Are religious individuals more or less likely to have extramarital affairs? • Do attractive professors get better teaching evaluations? • Does the higher price of cigarettes deter smoking? • What determines housing prices more: lot size or the number of bedrooms? • How do teenagers and older people differ in the way they use social media? • Who is more likely to use online dating services? • Why do some purchase iPhones and others Blackberry devices? • Does the presence of children influence a family’s spending on alcohol? For each problem, you’ll walk through defining your question and the answers you’ll need; exploring how others have approached similar challenges; selecting your data and methods; generating your statistics; organizing your report; and telling your story. Throughout, the focus is squarely on what matters most: transforming data into insights that are clear, accurate, and can be acted upon.

Making Sense of Humanity

And Other Philosophical Papers 1982-1993
Author: Bernard Williams
Publisher: Cambridge University Press
ISBN: 9780521478687
Category: Philosophy
Page: 251
View: 6141

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Collection of philosophical papers

Blip, Ping, and Buzz

Making Sense of Radar and Sonar
Author: Mark Denny
Publisher: JHU Press
ISBN: 9780801886652
Category: Science
Page: 274
View: 619

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With twenty years' experience explaining technical concepts to non-experts in the radar industry, Mark Denny is the perfect guide to understanding just how remote sensing -- radar or sonar -- works. Weaving together interesting history and simple science, Denny reveals the world of echolocation to the curious student, technology buff, and expert alike.

Dancing in Limbo

Making Sense of Life After Cancer
Author: Glenna Halvorson-Boyd,Lisa K. Hunter
Publisher: Jossey-Bass
ISBN: 9780787901035
Category: Health & Fitness
Page: 192
View: 4820

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Life After Cancer I immediately wanted to recommAnd this book to my patients. [It] will serve as a roadmap to help cancer patients anticipate feelings and stages of the coping process. It will help demystify the complex and often baffling set of experiences on the uncertain path of cancer survivorship. --Elisabeth Targ, M.D., Geraldine Brush Cancer Research Institute, California Pacific Medical Center An intimate and inspiring account of the authors' real-life experiences of surviving cancer. The authors provide a straightforward account of what life is like after the whirlwind of doctors' visits and radical treatments comes to an And.

Polarized

Making Sense of a Divided America
Author: James E. Campbell
Publisher: Princeton University Press
ISBN: 1400889278
Category: Political Science
Page: 336
View: 3296

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Many continue to believe that the United States is a nation of political moderates. In fact, it is a nation divided. It has been so for some time and has grown more so. This book provides a new and historically grounded perspective on the polarization of America, systematically documenting how and why it happened. Polarized presents commonsense benchmarks to measure polarization, draws data from a wide range of historical sources, and carefully assesses the quality of the evidence. Through an innovative and insightful use of circumstantial evidence, it provides a much-needed reality check to claims about polarization. This rigorous yet engaging and accessible book examines how polarization displaced pluralism and how this affected American democracy and civil society. Polarized challenges the widely held belief that polarization is the product of party and media elites, revealing instead how the American public in the 1960s set in motion the increase of polarization. American politics became highly polarized from the bottom up, not the top down, and this began much earlier than often thought. The Democrats and the Republicans are now ideologically distant from each other and about equally distant from the political center. Polarized also explains why the parties are polarized at all, despite their battle for the decisive median voter. No subject is more central to understanding American politics than political polarization, and no other book offers a more in-depth and comprehensive analysis of the subject than this one.

Checklist for Change

Making American Higher Education a Sustainable Enterprise
Author: Robert Zemsky
Publisher: Rutgers University Press
ISBN: 0813561353
Category: Education
Page: 240
View: 2099

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Almost every day American higher education is making news with a list of problems that includes the incoherent nature of the curriculum, the resistance of the faculty to change, and the influential role of the federal government both through major investments in student aid and intrusive policies. Checklist for Change not only diagnoses these problems, but also provides constructive recommendations for practical change. Robert Zemsky details the complications that have impeded every credible reform intended to change American higher education. He demythologizes such initiatives as the Morrill Act, the GI Bill, and the Higher Education Act of 1972, shedding new light on their origins and the ways they have shaped higher education in unanticipated and not commonly understood ways. Next, he addresses overly simplistic arguments about the causes of the problems we face and builds a convincing argument that well-intentioned actions have combined to create the current mess for which everyone is to blame. Using provocative case studies, Zemsky describes the reforms being implemented at a few institutions with the hope that these might serve as harbingers of the kinds of change needed: the University of Minnesota at Rochester’s compact curriculum in the health sciences only, Whittier College’s emphasis on learning outcomes, and the University of Wisconsin Oshkosh’s coherent overall curriculum. In conclusion, Zemsky describes the principal changes that must occur not singly but in combination. These include a fundamental recasting of federal financial aid; new mechanisms for better channeling the competition among colleges and universities; recasting the undergraduate curriculum; and a stronger, more collective faculty voice in governance that defines not why, but how the enterprise must change.

Data Smart

Using Data Science to Transform Information into Insight
Author: John W. Foreman
Publisher: John Wiley & Sons
ISBN: 1118839862
Category: Business & Economics
Page: 432
View: 7659

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Data Science gets thrown around in the press like it's magic. Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions. But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope. Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data. Each chapter will cover a different technique in a spreadsheet so you can follow along: Mathematical optimization, including non-linear programming and genetic algorithms Clustering via k-means, spherical k-means, and graph modularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, and bag-of-words models Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation Moving from spreadsheets into the R programming language You get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

The Myth of Judicial Activism

Making Sense of Supreme Court Decisions
Author: Kermit Roosevelt
Publisher: Yale University Press
ISBN: 9780300129564
Category: Law
Page: 273
View: 9048

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Constitutional scholar Kermit Roosevelt uses plain language and compelling examples to explain how the Constitution can be both a constant and an organic document, and takes a balanced look at controversial decisions through a compelling new lens of constitutional interpretation.

Making Sense of Factor Analysis

The Use of Factor Analysis for Instrument Development in Health Care Research
Author: Marjorie A. Pett,Nancy R. Lackey,John J. Sullivan
Publisher: SAGE
ISBN: 0761919503
Category: Education
Page: 348
View: 5788

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Making Sense of Factor Analysis: The Use of Factor Analysis for Instrument Development in Health Care Research presents a straightforward explanation of the complex statistical procedures involved in factor analysis. Authors Marjorie A. Pett, Nancy M. Lackey, and John J. Sullivan provide a step-by-step approach to analyzing data using statistical computer packages like SPSS and SAS. Emphasizing the interrelationship between factor analysis and test construction, the authors examine numerous practical and theoretical decisions that must be made to efficiently run and accurately interpret the outcomes of these sophisticated computer programs.

Is God a Moral Monster?

Making Sense of the Old Testament God
Author: Paul Copan
Publisher: Baker Books
ISBN: 9781441214546
Category: Religion
Page: 256
View: 3179

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A recent string of popular-level books written by the New Atheists have leveled the accusation that the God of the Old Testament is nothing but a bully, a murderer, and a cosmic child abuser. This viewpoint is even making inroads into the church. How are Christians to respond to such accusations? And how are we to reconcile the seemingly disconnected natures of God portrayed in the two testaments? In this timely and readable book, apologist Paul Copan takes on some of the most vexing accusations of our time, including: God is arrogant and jealous God punishes people too harshly God is guilty of ethnic cleansing God oppresses women God endorses slavery Christianity causes violence and more Copan not only answers God's critics, he also shows how to read both the Old and New Testaments faithfully, seeing an unchanging, righteous, and loving God in both.

Designing Data-Intensive Applications

The Big Ideas Behind Reliable, Scalable, and Maintainable Systems
Author: Martin Kleppmann
Publisher: "O'Reilly Media, Inc."
ISBN: 1491903104
Category: Computers
Page: 624
View: 6104

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Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures

Application of Big Data for National Security

A Practitioner’s Guide to Emerging Technologies
Author: Babak Akhgar,Gregory B. Saathoff,Hamid R Arabnia,Richard Hill,Andrew Staniforth,Petra Saskia Bayerl
Publisher: Butterworth-Heinemann
ISBN: 0128019735
Category: Political Science
Page: 316
View: 2852

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Application of Big Data for National Security provides users with state-of-the-art concepts, methods, and technologies for Big Data analytics in the fight against terrorism and crime, including a wide range of case studies and application scenarios. This book combines expertise from an international team of experts in law enforcement, national security, and law, as well as computer sciences, criminology, linguistics, and psychology, creating a unique cross-disciplinary collection of knowledge and insights into this increasingly global issue. The strategic frameworks and critical factors presented in Application of Big Data for National Security consider technical, legal, ethical, and societal impacts, but also practical considerations of Big Data system design and deployment, illustrating how data and security concerns intersect. In identifying current and future technical and operational challenges it supports law enforcement and government agencies in their operational, tactical and strategic decisions when employing Big Data for national security Contextualizes the Big Data concept and how it relates to national security and crime detection and prevention Presents strategic approaches for the design, adoption, and deployment of Big Data technologies in preventing terrorism and reducing crime Includes a series of case studies and scenarios to demonstrate the application of Big Data in a national security context Indicates future directions for Big Data as an enabler of advanced crime prevention and detection