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
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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 and Statistics in Psychology


Author: Gerry Mulhern,Brian Greer
Publisher: Macmillan International Higher Education
ISBN: 0230357997
Category: Psychology
Page: 320
View: 8086

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'I became a psychology student because I'm curious about why people behave as they do. Why am I expected to study statistics?' Statistics is one of the most useful elements of any psychology degree. This popular textbook will equip you with the tools needed not only to make sense of your own data and research, but also to think critically about the research and statistics you will encounter in everyday life. Features include: - Logical, intuitive organization of key statistical concepts and tests with an emphasis on understanding which test to use and why - Innovative graphic illustrations and insightful dialogues that help you to get to grips with statistics - Concise, easy-to-follow guidelines for making sense of SPSS - COverage of more complex tests and concepts for when you need to dig deeper Making Sense of Data and Statistics in Psychology will help you design experiments, analyse data with confidence and establish a solid grounding in statistics; it will become a valuable resource throughout your studies. Gerry Mulhern is Senior Lecturer in Psychology at Queen's University Belfast, UK, and was President of the British Psychological Society from 2010 to 2011. Brian Greer is Adjunct Professor in the Graduate School of Education at Portland State University, USA. He has taught statistics to psychology students for many years, and has published widely on mathematics education. At www.palgrave.com/psychology/mulhern2e, students and lecturers will find a wealth of resources, including additional data sets, extra guidance on tests and lecture slides.

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: 2433

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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 Data


Author: Donald J. Wheeler
Publisher: Spc Press
ISBN: 9780945320616
Category: Social Science
Page: 395
View: 8130

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This book addresses the isues of Data Analysis and SPC in a service setting. Emphasis is give to three basic questions of quality improvement: What do you want to accomplish? By what method? How will you know? 130 Examples and Case Histories from real businesses are used to illustrate the concepts. Readers discover where to start, what to measure, how to measure it, how to understand the measurement.

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
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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

A Self-Instruction Manual on the Interpretation of Epidemiological Data
Author: J. H. Abramson,Z. H. Abramson
Publisher: Oxford University Press
ISBN: 9780195145243
Category: Medical
Page: 367
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This self-instructional manual on the interpretation and use of epidemiologic data deals with the basic concepts and skills needed for the appraisal of published reports or one's own findings. Applications in clinical medicine, public health, community medicine, and research are all taken into consideration. Making Sense of Data is designed as a workbook of short exercises and instructional self-tests that introduce fundamental approaches and procedures in data interpretation and develop competency in working with epidemiologic tools. Basic concepts are presented in the first section, which also demonstrates the step-by-step assessment of data. The next section discusses rates and other simple measures, and the third shows how to judge their accuracy. Section IV and V deal with more complex issues of associations between variables and the appraisal of cause-effect relationships. Section VI deals with meta-analysis (the critical review and integration of the findings from separate studies) and section VII with the questions to be asked before deciding to apply study results in practice. Numerous changes have been made in this edition, including the addition of a section on the practical application of epidemiological findings, discussions of new topics (Cox proportional hazards regression, qualitative studies, ROC curves), and fresh examples.

Visual Insights

A Practical Guide to Making Sense of Data
Author: Katy Börner,David E. Polley
Publisher: MIT Press
ISBN: 026232024X
Category: Language Arts & Disciplines
Page: 312
View: 5666

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In the age of Big Data, the tools of information visualization offer us a macroscope to help us make sense of the avalanche of data available on every subject. This book offers a gentle introduction to the design of insightful information visualizations. It is the only book on the subject that teaches nonprogrammers how to use open code and open data to design insightful visualizations. Readers will learn to apply advanced data mining and visualization techniques to make sense of temporal, geospatial, topical, and network data. The book, developed for use in an information visualization MOOC, covers data analysis algorithms that enable extraction of patterns and trends in data, with chapters devoted to "when" (temporal data), "where" (geospatial data), "what" (topical data), and "with whom" (networks and trees); and to systems that drive research and development. Examples of projects undertaken for clients include an interactive visualization of the success of game player activity in World of Warcraft; a visualization of 311 number adoption that shows the diffusion of non-emergency calls in the United States; a return on investment study for two decades of HIV/AIDS research funding by NIAID; and a map showing the impact of the HiveNYC Learning Network. Visual Insights will be an essential resource on basic information visualization techniques for scholars in many fields, students, designers, or anyone who works with data.

Principles of Data Science


Author: Sinan Ozdemir
Publisher: Packt Publishing Ltd
ISBN: 1785888927
Category: Computers
Page: 388
View: 3259

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Learn the techniques and math you need to start making sense of your data About This Book Enhance your knowledge of coding with data science theory for practical insight into data science and analysis More than just a math class, learn how to perform real-world data science tasks with R and Python Create actionable insights and transform raw data into tangible value Who This Book Is For You should be fairly well acquainted with basic algebra and should feel comfortable reading snippets of R/Python as well as pseudo code. You should have the urge to learn and apply the techniques put forth in this book on either your own data sets or those provided to you. If you have the basic math skills but want to apply them in data science or you have good programming skills but lack math, then this book is for you. What You Will Learn Get to know the five most important steps of data science Use your data intelligently and learn how to handle it with care Bridge the gap between mathematics and programming Learn about probability, calculus, and how to use statistical models to control and clean your data and drive actionable results Build and evaluate baseline machine learning models Explore the most effective metrics to determine the success of your machine learning models Create data visualizations that communicate actionable insights Read and apply machine learning concepts to your problems and make actual predictions In Detail Need to turn your skills at programming into effective data science skills? Principles of Data Science is created to help you join the dots between mathematics, programming, and business analysis. With this book, you'll feel confident about asking—and answering—complex and sophisticated questions of your data to move from abstract and raw statistics to actionable ideas. With a unique approach that bridges the gap between mathematics and computer science, this books takes you through the entire data science pipeline. Beginning with cleaning and preparing data, and effective data mining strategies and techniques, you'll move on to build a comprehensive picture of how every piece of the data science puzzle fits together. Learn the fundamentals of computational mathematics and statistics, as well as some pseudocode being used today by data scientists and analysts. You'll get to grips with machine learning, discover the statistical models that help you take control and navigate even the densest datasets, and find out how to create powerful visualizations that communicate what your data means. Style and approach This is an easy-to-understand and accessible tutorial. It is a step-by-step guide with use cases, examples, and illustrations to get you well-versed with the concepts of data science. Along with explaining the fundamentals, the book will also introduce you to slightly advanced concepts later on and will help you implement these techniques in the real world.

Digital Marketing Analytics

Making Sense of Consumer Data in a Digital World
Author: Chuck Hemann,Ken Burbary
Publisher: Que Publishing
ISBN: 0134998650
Category: Business & Economics
Page: 272
View: 3630

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Distill Maximum Value from Your Digital Data! Do It Now! Why hasn’t all that data delivered a whopping competitive advantage? Because you’ve barely begun to use it, that’s why! Good news: neither have your competitors. It’s hard! But digital marketing analytics is 100% doable, it offers colossal opportunities, and all of the data is accessible to you. Chuck Hemann and Ken Burbary will help you chop the problem down to size, solve every piece of the puzzle, and integrate a virtually frictionless system for moving from data to decision, action to results! Scope it out, pick your tools, learn to listen, get the metrics right, and then distill your digital data for maximum value for everything from R&D to customer service to social media marketing! Prioritize—because you can’t measure and analyze everything Use analysis to craft experiences that profoundly reflect each customer’s needs, expectations, and behaviors Measure real digital media ROI: sales, leads, and customer satisfaction Track the performance of all paid, earned, and owned digital channels Leverage digital data way beyond PR and marketing: for strategic planning, product development, and HR Start optimizing digital content in real time Implement advanced tools, processes, and algorithms for accurately measuring influence Make the most of surveys, focus groups, and offline research synergies Focus new marketing investments where they’ll deliver the most value • Identify and understand your most important audiences across the digital ecosystem “Chuck and Ken lead marketers clearly and efficiently through the minefield of digital marketing measurement. And they do so with a lightness of touch and absence of jargon so rare in this overhyped, much-misunderstood ecosystem.” —Sam Knowles, Founder & MD of Insight Agents; author of Narrative by Numbers: How to Tell Powerful & Purposeful Stories with Data

Data Assimilation

Making Sense of Observations
Author: William Lahoz,Boris Khattatov,Richard Menard
Publisher: Springer Science & Business Media
ISBN: 9783540747031
Category: Science
Page: 718
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Data assimilation methods were largely developed for operational weather forecasting, but in recent years have been applied to an increasing range of earth science disciplines. This book will set out the theoretical basis of data assimilation with contributions by top international experts in the field. Various aspects of data assimilation are discussed including: theory; observations; models; numerical weather prediction; evaluation of observations and models; assessment of future satellite missions; application to components of the Earth System. References are made to recent developments in data assimilation theory (e.g. Ensemble Kalman filter), and to novel applications of the data assimilation method (e.g. ionosphere, Mars data assimilation).

Statistics

Making Sense of Data
Author: William F. Stout,Kenneth J. Travers,John I. Marden,Amy Goodwin
Publisher: Mobius Communications Limited
ISBN: 9781891304002
Category: Mathematics
Page: 722
View: 3708

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Making Sense of Multivariate Data Analysis

An Intuitive Approach
Author: John Spicer
Publisher: SAGE
ISBN: 9781412904018
Category: Mathematics
Page: 233
View: 2891

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'This book is a helpful guide to reading and understanding multivariate data analysis results in social and psychological research' --C. Y. Joanne Peng, Indiana University at Bloomington 'This book serves as a resource for readers who want to have an overall view of what encompasses multivariate analyses. The author has discussed some important issues rather philosophically (e.g., theory vs. data analysis). These points are valuable even for readers who have extensive training with multivariate analyses' --Jenn-Yun Tein, Arizona State University

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: 3752

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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 Research

What's Good, What's Not, and How To Tell the Difference
Author: Elaine K. McEwan,Patrick J. McEwan
Publisher: Corwin Press
ISBN: 148336092X
Category: Education
Page: 200
View: 505

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This book is for practitioners at all levels, from teachers making site-specific decisions to administrators making schoolwide and policy decisions.

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: 8495

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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 Sensors

End-to-End Algorithms and Infrastructure Design from Wearable-Devices to Data Centers
Author: Omesh Tickoo,Ravi Iyer
Publisher: Apress
ISBN: 1430265930
Category: Computers
Page: 117
View: 6986

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Make the most of the common architectures used for deriving meaningful data from sensors. This book provides you with the tools to understand how sensor data is converted into actionable knowledge and provides tips for in-depth work in this field. Making Sense of Sensors starts with an overview of the general pipeline to extract meaningful data from sensors. It then dives deeper into some commonly used sensors and algorithms designed for knowledge extraction. Practical examples and pointers to more information are used to outline the key aspects of Multimodal recognition. The book concludes with a discussion on relationship extraction, knowledge representation, and management. In today’s world we are surrounded by sensors collecting various types of data about us and our environments. These sensors are the primary input devices for wearable computers, IoT, and other mobile devices. The information is presented in way that allows readers to associate the examples with their daily lives for better understanding of the concepts. What You'll Learn Look at the general architecture for sensor based data Understand how data from common domains such as inertial, visual and audio is processed Master multi-modal recognition using multiple heterogeneous sensors Transition from recognition to knowledge through relationship understanding between entities Leverage different methods and tools for knowledge representation and management Who This Book Is For New college graduates and professionals interested in acquiring knowledge and the skills to develop innovative solutions around today's sensor-rich devices.

Making sense of qualitative data

complementary research strategies
Author: Amanda Coffey,Paul Atkinson
Publisher: Sage Publications, Inc
ISBN: 9780803970526
Category: Reference
Page: 206
View: 9272

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After a research project has been designed and the data have been gathered, what is the best way to transform the myriad varieties of data into something useful? Authors Amanda Coffey and Paul Atkinson underscore the diversity of approaches at the disposal of the qualitative researcher by using a single data set--doctoral students and faculty members in social anthropology--that they analyze using a number of techniques. User-friendly and accessible, Making Sense of Qualitative Data is not intended as a comprehensive cookbook of methods. It describes and illustrates a number of key, complementary approaches to qualitative data and offers practical advice on the many ways to analyze data, which the reader is encouraged to explore and enjoy. Practical and straightforward, with special attention paid to the possibilities in computer-aided analysis, Making Sense of Qualitative Data is an invaluable resource to students and professionals in qualitative and research methods, sociology, anthropology, communication, management, and education.

Data Insights

New Ways to Visualize and Make Sense of Data
Author: Hunter Whitney
Publisher: Newnes
ISBN: 0123877946
Category: Computers
Page: 320
View: 7878

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Data Insights: New Ways to Visualize and Make Sense of Data offers thought-provoking insights into how visualization can foster a clearer and more comprehensive understanding of data. The book offers perspectives from people with different backgrounds, including data scientists, statisticians, painters, and writers. It argues that all data is useless, or misleading, if we do not know what it means. Organized into seven chapters, the book explores some of the ways that data visualization and other emerging approaches can make data meaningful and therefore useful. It also discusses some fundamental ideas and basic questions in the data lifecycle; the process of interactions between people, data, and displays that lead to better questions and more useful answers; and the fundamentals, origins, and purposes of the basic building blocks that are used in data visualization. The reader is introduced to tried and true approaches to understanding users in the context of user interface design, how communications can get distorted, and how data visualization is related to thinking machines. Finally, the book looks at the future of data visualization by assessing its strengths and weaknesses. Case studies from business analytics, healthcare, network monitoring, security, and games, among others, as well as illustrations, thought-provoking quotes, and real-world examples are included. This book will prove useful to computer professionals, technical marketing professionals, content strategists, Web and product designers, and researchers. Demonstrates, with a variety of case studies, how visualizations can foster a clearer and more comprehensive understanding of data Answers the question, "How can data visualization help me?" with discussions of how it fits into a wide array of purposes and situations Makes the case that data visualization is not just about technology; it also involves a deeply human process

Making Sense of Cinema

Empirical Studies Into Film Spectators and Spectatorship
Author: CarrieLynn D. Reinhard,Christopher J. Olson
Publisher: Bloomsbury Publishing USA
ISBN: 1501320211
Category: Performing Arts
Page: 288
View: 6754

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Explores a variety of theological and methodological approaches to film spectatorship through a dialogue of international contributions.