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Author : Giandomenico Majone
Publisher : John Wiley & Sons
ISBN 13 :
Total Pages : 232 pages
Book Rating : 4.F/5 ( download)
Download or read book Pitfalls of Analysis written by Giandomenico Majone and published by John Wiley & Sons. This book was released on 1980 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Edward S. Quade
Publisher :
ISBN 13 :
Total Pages : 30 pages
Book Rating : 4.:/5 (417 download)
Download or read book Pitfalls of Analysis written by Edward S. Quade and published by . This book was released on 1959 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Ben Jones
Publisher : John Wiley & Sons
ISBN 13 : 1119278163
Total Pages : 272 pages
Book Rating : 4.1/5 (192 download)
Download or read book Avoiding Data Pitfalls written by Ben Jones and published by John Wiley & Sons. This book was released on 2019-11-19 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Avoid data blunders and create truly useful visualizations Avoiding Data Pitfalls is a reputation-saving handbook for those who work with data, designed to help you avoid the all-too-common blunders that occur in data analysis, visualization, and presentation. Plenty of data tools exist, along with plenty of books that tell you how to use them—but unless you truly understand how to work with data, each of these tools can ultimately mislead and cause costly mistakes. This book walks you step by step through the full data visualization process, from calculation and analysis through accurate, useful presentation. Common blunders are explored in depth to show you how they arise, how they have become so common, and how you can avoid them from the outset. Then and only then can you take advantage of the wealth of tools that are out there—in the hands of someone who knows what they're doing, the right tools can cut down on the time, labor, and myriad decisions that go into each and every data presentation. Workers in almost every industry are now commonly expected to effectively analyze and present data, even with little or no formal training. There are many pitfalls—some might say chasms—in the process, and no one wants to be the source of a data error that costs money or even lives. This book provides a full walk-through of the process to help you ensure a truly useful result. Delve into the "data-reality gap" that grows with our dependence on data Learn how the right tools can streamline the visualization process Avoid common mistakes in data analysis, visualization, and presentation Create and present clear, accurate, effective data visualizations To err is human, but in today's data-driven world, the stakes can be high and the mistakes costly. Don't rely on "catching" mistakes, avoid them from the outset with the expert instruction in Avoiding Data Pitfalls.
Author : Jay Cordes
Publisher : Oxford University Press, USA
ISBN 13 : 0198844395
Total Pages : 263 pages
Book Rating : 4.1/5 (988 download)
Download or read book The 9 Pitfalls of Data Science written by Jay Cordes and published by Oxford University Press, USA. This book was released on 2019-07-08 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data science has never had more influence on the world. Large companies are now seeing the benefit of employing data scientists to interpret the vast amounts of data that now exists. However, the field is so new and is evolving so rapidly that the analysis produced can be haphazard at best. The 9 Pitfalls of Data Science shows us real-world examples of what can go wrong. Written to be an entertaining read, this invaluable guide investigates the all too common mistakes of data scientists - who can be plagued by lazy thinking, whims, hunches, and prejudices - and indicates how they have been at the root of many disasters, including the Great Recession. Gary Smith and Jay Cordes emphasise how scientific rigor and critical thinking skills are indispensable in this age of Big Data, as machines often find meaningless patterns that can lead to dangerous false conclusions. The 9 Pitfalls of Data Science is loaded with entertaining tales of both successful and misguided approaches to interpreting data, both grand successes and epic failures. These cautionary tales will not only help data scientists be more effective, but also help the public distinguish between good and bad data science.
Author : Giandomenico Majone
Publisher :
ISBN 13 :
Total Pages : 22 pages
Book Rating : 4.:/5 (299 download)
Download or read book Pitfalls of Analysis and the Analysis of Pitfalls written by Giandomenico Majone and published by . This book was released on 1977 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : United States. Office of Educational Research and Improvement
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (524 download)
Download or read book PITFALLS OF DATA ANALYSIS. ERIC written by United States. Office of Educational Research and Improvement and published by . This book was released on 1998* with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Herman Kahn
Publisher :
ISBN 13 :
Total Pages : 55 pages
Book Rating : 4.:/5 (72 download)
Download or read book Ten Common Pitfalls written by Herman Kahn and published by . This book was released on 1957 with total page 55 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Justin Grimmer
Publisher : Princeton University Press
ISBN 13 : 0691207550
Total Pages : 360 pages
Book Rating : 4.6/5 (912 download)
Download or read book Text as Data written by Justin Grimmer and published by Princeton University Press. This book was released on 2022-03-29 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide for using computational text analysis to learn about the social world From social media posts and text messages to digital government documents and archives, researchers are bombarded with a deluge of text reflecting the social world. This textual data gives unprecedented insights into fundamental questions in the social sciences, humanities, and industry. Meanwhile new machine learning tools are rapidly transforming the way science and business are conducted. Text as Data shows how to combine new sources of data, machine learning tools, and social science research design to develop and evaluate new insights. Text as Data is organized around the core tasks in research projects using text—representation, discovery, measurement, prediction, and causal inference. The authors offer a sequential, iterative, and inductive approach to research design. Each research task is presented complete with real-world applications, example methods, and a distinct style of task-focused research. Bridging many divides—computer science and social science, the qualitative and the quantitative, and industry and academia—Text as Data is an ideal resource for anyone wanting to analyze large collections of text in an era when data is abundant and computation is cheap, but the enduring challenges of social science remain. Overview of how to use text as data Research design for a world of data deluge Examples from across the social sciences and industry
Author : D. A. De Vaus
Publisher : SAGE
ISBN 13 : 9780761959380
Total Pages : 436 pages
Book Rating : 4.9/5 (593 download)
Download or read book Analyzing Social Science Data written by D. A. De Vaus and published by SAGE. This book was released on 2002-09-17 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abridged Contents PART ONE: HOW TO PREPARE DATA FOR ANALYSIS\PART TWO: HOW TO PREPARE VARIABLE FOR ANALYSIS\PART THREE: HOW TO REDUCE THE AMOUNT OF DATA TO ANALYZE\PART FOUR: HOW AND WHEN TO GENERALIZE\PART FIVE: HOW TO ANALYZE A SINGLE VARIABLE\PART SIX: HOW TO ANALYZE TWO VARIABLES\PART SEVEN: HOW TO CARRY OUT MULTIVARIATE ANALYSIS
Author : Clay Helberg
Publisher :
ISBN 13 :
Total Pages : 6 pages
Book Rating : 4.:/5 (13 download)
Download or read book Pitfalls of Data Analysis written by Clay Helberg and published by . This book was released on 1996 with total page 6 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Horst Langer
Publisher : Elsevier
ISBN 13 : 0128118431
Total Pages : 350 pages
Book Rating : 4.1/5 (281 download)
Download or read book Advantages and Pitfalls of Pattern Recognition written by Horst Langer and published by Elsevier. This book was released on 2019-11-23 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advantages and Pitfalls of Pattern Recognition presents various methods of pattern recognition and classification, useful to geophysicists, geochemists, geologists, geographers, data analysts, and educators and students of geosciences. Scientific and technological progress has dramatically improved the knowledge of our planet with huge amounts of digital data available in various fields of Earth Sciences, such as geology, geophysics, and geography. This has led to a new perspective of data analysis, requiring specific techniques that take several features into consideration rather than single parameters. Pattern recognition techniques offer a suitable key for processing and extracting useful information from the data of multivariate analysis. This book explores both supervised and unsupervised pattern recognition techniques, while providing insight into their application. Offers real-world examples of techniques for pattern recognition and handling multivariate data Includes examples, applications, and diagrams to enhance understanding Provides an introduction and access to relevant software packages
Author : Michael Borenstein
Publisher :
ISBN 13 : 9781733436700
Total Pages : 409 pages
Book Rating : 4.4/5 (367 download)
Download or read book Common Mistakes in Meta-Analysis written by Michael Borenstein and published by . This book was released on 2019-08-15 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Scott B. Morris
Publisher : Psychology Press
ISBN 13 : 1315301415
Total Pages : 381 pages
Book Rating : 4.3/5 (153 download)
Download or read book Adverse Impact Analysis written by Scott B. Morris and published by Psychology Press. This book was released on 2016-12-01 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: Compliance with federal equal employment opportunity regulations, including civil rights laws and affirmative action requirements, requires collection and analysis of data on disparities in employment outcomes, often referred to as adverse impact. While most human resources (HR) practitioners are familiar with basic adverse impact analysis, the courts and regulatory agencies are increasingly relying on more sophisticated methods to assess disparities. Employment data are often complicated, and can include a broad array of employment actions (e.g., selection, pay, promotion, termination), as well as data that span multiple protected groups, settings, and points in time. In the era of "big data," the HR analyst often has access to larger and more complex data sets relevant to employment disparities. Consequently, an informed HR practitioner needs a richer understanding of the issues and methods for conducting disparity analyses. This book brings together the diverse literature on disparity analysis, spanning work from statistics, industrial/organizational psychology, human resource management, labor economics, and law, to provide a comprehensive and integrated summary of current best practices in the field. Throughout, the description of methods is grounded in the legal context and current trends in employment litigation and the practices of federal regulatory agencies. The book provides guidance on all phases of disparity analysis, including: How to structure diverse and complex employment data for disparity analysis How to conduct both basic and advanced statistical analyses on employment outcomes related to employee selection, promotion, compensation, termination, and other employment outcomes How to interpret results in terms of both practical and statistical significance Common practical challenges and pitfalls in disparity analysis and strategies to deal with these issues
Author : National Research Council
Publisher : National Academies Press
ISBN 13 : 0309287812
Total Pages : 191 pages
Book Rating : 4.3/5 (92 download)
Download or read book Frontiers in Massive Data Analysis written by National Research Council and published by National Academies Press. This book was released on 2013-09-03 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.
Author : Ian Dey
Publisher : Routledge
ISBN 13 : 1134931468
Total Pages : 309 pages
Book Rating : 4.1/5 (349 download)
Download or read book Qualitative Data Analysis written by Ian Dey and published by Routledge. This book was released on 2003-09-02 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Qualitative Data Analysis shows that learning how to analyse qualitative data by computer can be fun. Written in a stimulating style, with examples drawn mainly from every day life and contemporary humour, it should appeal to a wide audience.
Download or read book International Series on Applied Systems Analysis written by and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Matt Taddy
Publisher : McGraw Hill Professional
ISBN 13 : 1260452786
Total Pages : 384 pages
Book Rating : 4.2/5 (64 download)
Download or read book Business Data Science: Combining Machine Learning and Economics to Optimize, Automate, and Accelerate Business Decisions written by Matt Taddy and published by McGraw Hill Professional. This book was released on 2019-08-23 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Use machine learning to understand your customers, frame decisions, and drive value The business analytics world has changed, and Data Scientists are taking over. Business Data Science takes you through the steps of using machine learning to implement best-in-class business data science. Whether you are a business leader with a desire to go deep on data, or an engineer who wants to learn how to apply Machine Learning to business problems, you’ll find the information, insight, and tools you need to flourish in today’s data-driven economy. You’ll learn how to: •Use the key building blocks of Machine Learning: sparse regularization, out-of-sample validation, and latent factor and topic modeling•Understand how use ML tools in real world business problems, where causation matters more that correlation•Solve data science programs by scripting in the R programming language Today’s business landscape is driven by data and constantly shifting. Companies live and die on their ability to make and implement the right decisions quickly and effectively. Business Data Science is about doing data science right. It’s about the exciting things being done around Big Data to run a flourishing business. It’s about the precepts, principals, and best practices that you need know for best-in-class business data science.
