[Judea Pearl] download The Book of Why The New Science of Cause and Effect Ebook – Kindle eBook and Epub

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Stions 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 W. This is an engaging well articulated discussion of causal inference what it is what the available tools are RCTs IVs matching etc how they have changed over the years and how they could be improved The bits that tell the history of causal inference are especially illuminating I learned a lot of stats in grad school but very little about the struggles and accidents that produced the tools I learned Pearl helps put much of that into contextNow Pearl s intended audience is clearly the machine learning community Much of what he says will not sound particularly Earth shattering to people in or from the social sciences You can t learn causality from data alone you need a model is one of the book s core messages It s hard to see an economist or political scientist disagreeing with it You come up with a theory you think up its observable implications you test them Even Pearl s proposal that we use mediation analysis won t sound exactly novel Social scientists have been doing that they just don t use that name for it they call it testing the theory s microfoundations Now having abandoned political science and lived among the machine learning people for four years now I can see how Pearl s message is important to his intended audience And social scientists should read the book too because it intelligently discusses the limitations of tools like RCTs and matchingIn the end what Pearl proposes that we use our knowledge of how the world works in order to formulate and test hypotheses may turn out to be deservedly influential in the machine learning community but it won t help fix the core problem with the social sciences ie that social scientists can always twist their hypotheses not to mention the very uestions they ask to accomodate their pet world views And when the DemocratRepublican ratio is 61 as it is in political science we can t trust that people will keep each other honest they won t Pearl discusses in passing the possibility that some day we may have machine learning algorithms capable of producing their own causal models Maybe then the social sciences will be worth the money they cost taxpayers

free read The Book of Why The New Science of Cause and Effect

The Book of Why The New Science of Cause and Effect

E 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 ue. I ve never met Pearl but having read a couple of his books I m pretty sure he s an asshole His anger and bitterness comes through very clearly in his book he spends as much space naming and vilifying his professional enemies both living and dead as he does explaining his work This is a real shame because his work is actually uite good and deserves a popular presentation sadly the sanctimony in this book is almost unbearable and there is no humor to lighten itUnfortunately I don t have an alternative to recommend instead I think your best bet is to read chapters 14 and 6 and keep a bottle of antacid handy

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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 than a century has led to a virtual prohibition on causal talk Today that taboo is dead Th. I enjoyed this book It did everything a good book should do it provides understandable examples entertaining side notes applications to the real world something useful that is novellittle known The book could have been better 5 stars if it was concise explained the general algorithms for mediation analysis independence testing transfer explained the relationship of causal inference to calculus and spent less time on its whig history and adversarial narrativeI think Judea s main point was Correlation does not imply causation unless you can control the confounders for this you need a causal model This means you can make causal inferences from data but you just need to make some assumptions Currently I feel like I understand the motivation and potential power of causal inference but I do not understand the details But thanks to this book I now have the motivation to stare at the math for as long as it takes or a few weeks For some thoughts see my blog


10 thoughts on “The Book of Why The New Science of Cause and Effect

  1. says:

    I had high hopes for this book I've been interested in causal inference for a number of years and I think it's an field that could drastically improve the practice of statistical science if its techniues became widely adopted A popular book on

  2. says:

    Failed revolutionIn an old joke an engineer a physicist and an economist are marooned on a desert island with canned food They are trying to figure out the best way to open the cans and while the engineer and the physicist propose various mechanical schemes to get the job done the economist says Let's assume we have a can opener Judea Pearl's approach to causal inference brings that joke to mind His causal calculus begins with

  3. says:

    I enjoyed this book It did everything a good book should do it provides; understandable examples entertaining side notes applications to the real world something useful that is novellittle known The book could have been better 5 stars if it was concise explained the general algorithms for; mediation analysis independence testing transfer explained the relationship of causal inference to calculus and spent less time on its whig

  4. says:

    I've never met Pearl but having read a couple of his books I'm pretty sure he's an asshole His anger and bitterness comes through ve

  5. says:

    There were some real flaws with this book that bothered me to no end I had no problem following his statistical examples and how to think about data analysis in the way the author suggests we all should I even enjoyed it when the author connected what he called Smart Artificial Intelligence to his overall causal theory and I enjoyed the book when he alluded in passing to the importance of solving the PNP problem and how

  6. says:

    Here is an excellent book by a renowned expert but potentially with deep fundamental flaws and conclusions The reviewer is likely mist

  7. says:

    There are great ideas in this book I'm not an expert on causality or statistics but I found the idea of modeling causality using a directed graph and using that graph as a tool for both a determining valid controls in experimental data and b p

  8. says:

    This review is for the audio version This topic is very interesting but audio is a terrible format for this book The narrator is reading out euations The whole point of the book is to use diagrams There is a PDF with the au

  9. says:

    This is an engaging well articulated discussion of causal inference what it is what the available tools are RCTs IVs matching etc how they have changed over the years and how they could be improved The bits that tell the history of causal inference are especially illuminating; I learned a lot of stats in grad school but very little about the struggles and accidents that produced the tools I learned Pearl helps put muc

  10. says:

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