Correlation Is Not Causation


Correlation Is Not Causation
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Correlation Is Not Causation


Correlation Is Not Causation
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Author : Lee Baker
language : en
Publisher: Lee Baker
Release Date :

Correlation Is Not Causation written by Lee Baker and has been published by Lee Baker this book supported file pdf, txt, epub, kindle and other format this book has been release on with Education categories.


Correlation Is Not Causation. You know it and I know it, and yet we are constantly having to be reminded of it because we can’t seem to help but get it wrong. How many times have you heard someone really smart say something like ‘wow, this correlation has a p-value of 0.000001 so A must be causing B…’? It’s not our fault though – we’re only human. We seek explanation for patterns and events that happen around us, and if something defies logic, we try to find a reason why it might make sense. If something doesn’t add up, we make it up. OK, so if correlation does not necessarily imply causation, there must be a reason for that, and there must be something that is causing what we observe. That is what this book is all about. If we discover a correlation between a pair of variables there are five alternatives to one being the direct cause of the other, and we’ll unmask all five in this book. Then, once we understand each of these alternatives, we’ll formulate a plan to discover whether we have a direct causal link or whether there is some other explanation. Correlation Is Not Causation explains how to systematically test for the five most common correlation-causation pitfalls that even the pros fall into (occasionally). We’ll learn to create strategies to analyse the data and interpret the results in a way that is easy to understand. Best of all, there is no technical or statistical jargon – it is written in plain English. It is packed with visually intuitive examples and makes no assumptions about your previous experience with correlations – in short, it is perfect for beginners! Discover the world of correlation and causation. Get this book, TODAY!



Spurious Correlations


Spurious Correlations
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Author : Tyler Vigen
language : en
Publisher: Hachette Books
Release Date : 2015-05-12

Spurious Correlations written by Tyler Vigen and has been published by Hachette Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-12 with Humor categories.


"Spurious Correlations ... is the most fun you'll ever have with graphs."--Bustle Military intelligence analyst and Harvard Law student Tyler Vigen illustrates the golden rule that "correlation does not equal causation" through hilarious graphs inspired by his viral website. Is there a correlation between Nic Cage films and swimming pool accidents? What about beef consumption and people getting struck by lightning? Absolutely not. But that hasn't stopped millions of people from going to tylervigen.com and asking, "Wait, what?" Vigen has designed software that scours enormous data sets to find unlikely statistical correlations. He began pulling the funniest ones for his website and has since gained millions of views, hundreds of thousands of likes, and tons of media coverage. Subversive and clever, Spurious Correlations is geek humor at its finest, nailing our obsession with data and conspiracy theory.



Introduction To Data Science


Introduction To Data Science
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Author : Rafael A. Irizarry
language : en
Publisher: CRC Press
Release Date : 2019-11-20

Introduction To Data Science written by Rafael A. Irizarry and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-20 with Mathematics categories.


Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert.



Actual Causality


Actual Causality
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Author : Joseph Y. Halpern
language : en
Publisher: MIT Press
Release Date : 2019-02-19

Actual Causality written by Joseph Y. Halpern and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-19 with Philosophy categories.


A new approach for defining causality and such related notions as degree of responsibility, degrees of blame, and causal explanation. Causality plays a central role in the way people structure the world; we constantly seek causal explanations for our observations. But what does it even mean that an event C “actually caused” event E? The problem of defining actual causation goes beyond mere philosophical speculation. For example, in many legal arguments, it is precisely what needs to be established in order to determine responsibility. The philosophy literature has been struggling with the problem of defining causality since Hume. In this book, Joseph Halpern explores actual causality, and such related notions as degree of responsibility, degree of blame, and causal explanation. The goal is to arrive at a definition of causality that matches our natural language usage and is helpful, for example, to a jury deciding a legal case, a programmer looking for the line of code that cause some software to fail, or an economist trying to determine whether austerity caused a subsequent depression. Halpern applies and expands an approach to causality that he and Judea Pearl developed, based on structural equations. He carefully formulates a definition of causality, and building on this, defines degree of responsibility, degree of blame, and causal explanation. He concludes by discussing how these ideas can be applied to such practical problems as accountability and program verification. Technical details are generally confined to the final section of each chapter and can be skipped by non-mathematical readers.



Calling Bullshit


Calling Bullshit
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Author : Carl T. Bergstrom
language : en
Publisher: Random House
Release Date : 2020-08-04

Calling Bullshit written by Carl T. Bergstrom and has been published by Random House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-04 with Political Science categories.


Bullshit isn’t what it used to be. Now, two science professors give us the tools to dismantle misinformation and think clearly in a world of fake news and bad data. “A modern classic . . . a straight-talking survival guide to the mean streets of a dying democracy and a global pandemic.”—Wired Misinformation, disinformation, and fake news abound and it’s increasingly difficult to know what’s true. Our media environment has become hyperpartisan. Science is conducted by press release. Startup culture elevates bullshit to high art. We are fairly well equipped to spot the sort of old-school bullshit that is based in fancy rhetoric and weasel words, but most of us don’t feel qualified to challenge the avalanche of new-school bullshit presented in the language of math, science, or statistics. In Calling Bullshit, Professors Carl Bergstrom and Jevin West give us a set of powerful tools to cut through the most intimidating data. You don’t need a lot of technical expertise to call out problems with data. Are the numbers or results too good or too dramatic to be true? Is the claim comparing like with like? Is it confirming your personal bias? Drawing on a deep well of expertise in statistics and computational biology, Bergstrom and West exuberantly unpack examples of selection bias and muddled data visualization, distinguish between correlation and causation, and examine the susceptibility of science to modern bullshit. We have always needed people who call bullshit when necessary, whether within a circle of friends, a community of scholars, or the citizenry of a nation. Now that bullshit has evolved, we need to relearn the art of skepticism.



Causal Inference


Causal Inference
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Author : Scott Cunningham
language : en
Publisher: Yale University Press
Release Date : 2021-01-26

Causal Inference written by Scott Cunningham and has been published by Yale University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-26 with Business & Economics categories.


An accessible, contemporary introduction to the methods for determining cause and effect in the social sciences "Causation versus correlation has been the basis of arguments--economic and otherwise--since the beginning of time. Causal Inference: The Mixtape uses legit real-world examples that I found genuinely thought-provoking. It's rare that a book prompts readers to expand their outlook; this one did for me."--Marvin Young (Young MC) Causal inference encompasses the tools that allow social scientists to determine what causes what. In a messy world, causal inference is what helps establish the causes and effects of the actions being studied--for example, the impact (or lack thereof) of increases in the minimum wage on employment, the effects of early childhood education on incarceration later in life, or the influence on economic growth of introducing malaria nets in developing regions. Scott Cunningham introduces students and practitioners to the methods necessary to arrive at meaningful answers to the questions of causation, using a range of modeling techniques and coding instructions for both the R and the Stata programming languages.



Facts And Figures


Facts And Figures
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Author :
language : en
Publisher:
Release Date : 1972

Facts And Figures written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1972 with categories.




The Oxford Handbook Of Causation


The Oxford Handbook Of Causation
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Author : Helen Beebee
language : en
Publisher: OUP Oxford
Release Date : 2012-01-12

The Oxford Handbook Of Causation written by Helen Beebee and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-12 with Philosophy categories.


Causation is a central topic in many areas of philosophy. In metaphysics, philosophers want to know what causation is, and how it is related to laws of nature, probability, action, and freedom of the will. In epistemology, philosophers investigate how causal claims can be inferred from statistical data, and how causation is related to perception, knowledge and explanation. In the philosophy of mind, philosophers want to know whether and how the mind can be said to have causal efficacy, and in ethics, whether there is a moral distinction between acts and omissions and whether the moral value of an act can be judged according to its consequences. And causation is a contested concept in other fields of enquiry, such as biology, physics, and the law. This book provides an in-depth and comprehensive overview of these and other topics, as well as the history of the causation debate from the ancient Greeks to the logical empiricists. The chapters provide surveys of contemporary debates, while often also advancing novel and controversial claims; and each includes a comprehensive bibliography and suggestions for further reading. The book is thus the most comprehensive source of information about causation currently available, and will be invaluable for upper-level undergraduates through to professional philosophers.



Cause And Correlation In Biology


Cause And Correlation In Biology
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Author : Bill Shipley
language : en
Publisher: Cambridge University Press
Release Date : 2002-08

Cause And Correlation In Biology written by Bill Shipley and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-08 with Mathematics categories.


This book goes beyond the truism that 'correlation does not imply causation' and explores the logical and methodological relationships between correlation and causation. It presents a series of statistical methods that can test, and potentially discover, cause-effect relationships between variables in situations in which it is not possible to conduct randomised or experimentally controlled experiments. Many of these methods are quite new and most are generally unknown to biologists. In addition to describing how to conduct these statistical tests, the book also puts the methods into historical context and explains when they can and cannot justifiably be used to test or discover causal claims. Written in a conversational style that minimises technical jargon, the book is aimed at practising biologists and advanced students, and assumes only a very basic knowledge of introductory statistics.



The Phantom Pattern Problem


The Phantom Pattern Problem
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Author : Gary Smith
language : en
Publisher: Oxford University Press, USA
Release Date : 2020-08-18

The Phantom Pattern Problem written by Gary Smith and has been published by Oxford University Press, USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-18 with Data mining categories.


Patterns in data are often used as evidence, but how can you tell if that evidence is worth believing? The Phantom Pattern Problem helps readers avoid being duped by data, tricked into worthless investing strategies, or scared out of getting vaccinations. Becoming a sceptical consumer of data is important in this age of Big Data.