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Author: Heinz Fassmann
Publisher: Amsterdam University Press
ISBN: 9089640525
Category : Mathematics
Languages : en
Pages : 319
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Book Description
"Worldwide harmonisation of migration statistics is something international bodies dream of. And yet, attempts by organisations needing comparative data have not proven very successful thus far. More than just problematising the incomparability of migrati
Author: Heinz Fassmann
Publisher: Amsterdam University Press
ISBN: 9089640525
Category : Mathematics
Languages : en
Pages : 319
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Book Description
"Worldwide harmonisation of migration statistics is something international bodies dream of. And yet, attempts by organisations needing comparative data have not proven very successful thus far. More than just problematising the incomparability of migrati
Author: William Kent
Publisher: North Holland
ISBN:
Category : Computers
Languages : en
Pages : 238
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Book Description
The nature of an information system; Naming; Relationships; Attributes; Types and categories and sets; Models; The record model; The other three popular models; The modelling of relationships; Elementary concepts; Philosophy.
Author: Darrell Huff
Publisher: W. W. Norton & Company
ISBN: 0393070875
Category : Mathematics
Languages : en
Pages : 144
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Book Description
If you want to outsmart a crook, learn his tricks—Darrell Huff explains exactly how in the classic How to Lie with Statistics. From distorted graphs and biased samples to misleading averages, there are countless statistical dodges that lend cover to anyone with an ax to grind or a product to sell. With abundant examples and illustrations, Darrell Huff’s lively and engaging primer clarifies the basic principles of statistics and explains how they’re used to present information in honest and not-so-honest ways. Now even more indispensable in our data-driven world than it was when first published, How to Lie with Statistics is the book that generations of readers have relied on to keep from being fooled.
Author: Ben Jones
Publisher: John Wiley & Sons
ISBN: 1119278163
Category : Business & Economics
Languages : en
Pages : 272
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Book Description
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: James R. Thompson
Publisher: John Wiley & Sons
ISBN: 9780471601050
Category : Mathematics
Languages : en
Pages : 268
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Book Description
A hands-on approach to the basic principles of empirical model building. Includes a series of real-world statistical problems illustrating modeling skills and techniques. Covers models of growth and decay, systems where competition and interaction add to the complexity of the model, and discusses both classical and nonclassical data analysis methods.
Author: David A. Freedman
Publisher: Cambridge University Press
ISBN: 1139477315
Category : Mathematics
Languages : en
Pages : 459
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Book Description
This lively and engaging book explains the things you have to know in order to read empirical papers in the social and health sciences, as well as the techniques you need to build statistical models of your own. The discussion in the book is organized around published studies, as are many of the exercises. Relevant journal articles are reprinted at the back of the book. Freedman makes a thorough appraisal of the statistical methods in these papers and in a variety of other examples. He illustrates the principles of modelling, and the pitfalls. The discussion shows you how to think about the critical issues - including the connection (or lack of it) between the statistical models and the real phenomena. The book is written for advanced undergraduates and beginning graduate students in statistics, as well as students and professionals in the social and health sciences.
Author: Deborah G. Mayo
Publisher: Cambridge University Press
ISBN: 1108563309
Category : Mathematics
Languages : en
Pages : 503
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Book Description
Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.
Author: Joseph Fried
Publisher: Algora Publishing
ISBN: 0875866034
Category : Political Science
Languages : en
Pages : 384
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Book Description
Are Democrats more tolerant than Republicans? Are they more intelligent? Who spends more time at work and who spends more time watching TV? Why are Republicans happier? Who benefits more from Social Security? All of these questions, and many more, are answered in Democrats and Republicans - Rhetoric and Reality. It uses authoritative survey evidence and statistics to compare the conduct and achievements of the Democratic and Republican constituencies. Many of the findings are surprising. For example, Democrats and Republicans have different tendencies with regard to trust, self-esteem, "apparent intelligence," political knowledge, mental health, happiness, work hours, charity, and even body mass index. These general differences are quantifiable and statistically significant. The author principally relied on data from the General Social Survey and the American National Election Studies, rounded out by surveys conducted by the Pew Research Center for the People and the Press, the Gallup Organization, the Institute for Public Policy and Social Research, Harris Interactive, and other organizations. Although the book is aimed at the popular market, it has all of the supporting references and statistical significance of an academic work. Interspersed among the findings are quotations from pundits, politicians, philosophers, celebrities, fruitcakes, etc. Although some of this rhetoric is strident, the book's overall tone is objective - a refreshing alternative to the bombastic polemics we often see in modern political works. The last chapter comprises several constructive lessons that can be learned from the various Democratic-Republican comparisons. This is the most comprehensive and authoritative book written about the constituencies of our two major political parties. It should be in the personal library of anyone who is interested in American politics
Author: Judea Pearl
Publisher: Basic Books
ISBN: 0465097618
Category : Computers
Languages : en
Pages : 465
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Book Description
A Turing Award-winning computer scientist and statistician shows how understanding causality has revolutionized science and will revolutionize artificial intelligence "Correlation is not causation." This mantra, chanted by scientists for more than a century, has led to a virtual prohibition on causal talk. Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality -- the study of cause and effect -- on a firm scientific basis. His work explains how we can know easy things, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl's work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and key to artificial intelligence. Anyone who wants to understand either needs The Book of Why.
Author: Edwin Diday
Publisher: John Wiley & Sons
ISBN: 1119694965
Category : Business & Economics
Languages : en
Pages : 232
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Book Description
Data science unifies statistics, data analysis and machine learning to achieve a better understanding of the masses of data which are produced today, and to improve prediction. Special kinds of data (symbolic, network, complex, compositional) are increasingly frequent in data science. These data require specific methodologies, but there is a lack of reference work in this field. Advances in Data Science fills this gap. It presents a collection of up-to-date contributions by eminent scholars following two international workshops held in Beijing and Paris. The 10 chapters are organized into four parts: Symbolic Data, Complex Data, Network Data and Clustering. They include fundamental contributions, as well as applications to several domains, including business and the social sciences.
