Spurious Correlations

Download Spurious Correlations PDF Online Free

Author :
Release : 2015-05-12
Genre : Humor
Kind :
Book Rating : 458/5 ( reviews)

Spurious Correlations - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Spurious Correlations write by Tyler Vigen. This book was released on 2015-05-12. Spurious Correlations available in PDF, EPUB and Kindle. "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.

Correlation Is Not Causation

Download Correlation Is Not Causation PDF Online Free

Author :
Release :
Genre : Education
Kind :
Book Rating : /5 ( reviews)

Correlation Is Not Causation - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Correlation Is Not Causation write by Lee Baker. This book was released on . Correlation Is Not Causation available in PDF, EPUB and Kindle. 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!

Causal Inference

Download Causal Inference PDF Online Free

Author :
Release : 2021-01-26
Genre : Business & Economics
Kind :
Book Rating : 888/5 ( reviews)

Causal Inference - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Causal Inference write by Scott Cunningham. This book was released on 2021-01-26. Causal Inference available in PDF, EPUB and Kindle. 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.

Introduction to Data Science

Download Introduction to Data Science PDF Online Free

Author :
Release : 2019-11-20
Genre : Mathematics
Kind :
Book Rating : 039/5 ( reviews)

Introduction to Data Science - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Introduction to Data Science write by Rafael A. Irizarry. This book was released on 2019-11-20. Introduction to Data Science available in PDF, EPUB and Kindle. 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.

Cause and Correlation in Biology

Download Cause and Correlation in Biology PDF Online Free

Author :
Release : 2002-08
Genre : Mathematics
Kind :
Book Rating : 211/5 ( reviews)

Cause and Correlation in Biology - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Cause and Correlation in Biology write by Bill Shipley. This book was released on 2002-08. Cause and Correlation in Biology available in PDF, EPUB and Kindle. 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.