The Seven Pillars of Statistical Wisdom

Posted on 17 May 2017 by Stephen M. Stigler

What gives statistics its unity as a science Stephen Stigler sets forth the seven foundational ideas of statistics a scientific discipline related to but distinct from mathematics and computer science.Even the most basic idea aggregation, exemplified by averaging is counterintuitive It allows one to gain information by discarding information, namely, the individuality of the observations Stigler s second pillar, information measurement, challenges the importance of big data by noting that observations are not all equally important the amount of information in a data set is often proportional to only the square root of the number of observations, not the absolute number The third idea is likelihood, the calibration of inferences with the use of probability Intercomparison is the principle that statistical comparisons do not need to be made with respect to an external standard The fifth pillar is regression, both a paradox tall parents on average produce shorter children tall children on average have shorter parents and the basis of inference, including Bayesian inference and causal reasoning The sixth concept captures the importance of experimental design for example, by recognizing the gains to be had from a combinatorial approach with rigorous randomization The seventh idea is the residual the notion that a complicated phenomenon can be simplified by subtracting the effect of known causes, leaving a residual phenomenon that can be explained easily The Seven Pillars of Statistical Wisdom presents an original, unified account of statistical science that will fascinate the interested layperson and engage the professional statistician. Download The Seven Pillars of Statistical Wisdom author Stephen M. Stigler – kino-fada.fr As a PhD student in Statistics, I found this book absolutely fascinating Seeing the conceptual linkages between statistical topics, and how one piece of research leads to another, was really revealing It s also written in a clear although there s a little notation fashion, so people can take home the stories of statistical wisdom, as opposed to the details of the methodology I now fully appreciate simply how revolutionary Galton s analysis was, and the same goes for inter comparison Indeed As a PhD student in Statistics, I found this book absolutely fascinating Seeing the conceptual linkages between statistical topics, and how one piece of research leads to another, was really revealing It s also written in a clear although there s a little notation fashion, so people can take home the stories of statistical wisdom, as opposed to the details of the methodology I now fully appreciate simply how revolutionary Galton s analysis was, and the same goes for inter comparison Indeed, seeing the relationship between calculation the standard error leading to the bootstrap, cross validation, was something I would have never thought of It s just fascinating to see the linkages between ideas in statistics relating to one another The design experiment was also great, with a real insight into Fisher s opportunism and ideas When he talks about asking nature a well thought out questionnaire , and...Kind of a disappointment for me I was hoping for statistical inspiration, or at least some ideas to guide my day today practice.For me this was less statistical wisdom,a thematic history of statistics, even if it has some good illustrations of the impact of the 7 key themes For me wisdom is that applied knowledge, and some advice on pros and cons.Hardly worthless Well written, and summarises an incredible amount of information effectively, just not what I was hoping for Maybe it ll ben Kind of a disappointment for me I was hoping for statistical inspiration, or at least some ideas to guid...Written by the author of The History of Statistics The Measurement of Uncertainty before 1900 , it seems to mostly cover new ground, or at least cover it differently Most of the stories related are new to me fine, it s been a while since I read his previous book.Stigler breaks statistics up into seven separate areas and traces the history of each aggregation, likelihood, experimental design, etc There was a really interesting story about the development of Bayesian statistics Philosopher Written by the author of The History of Statistics The Measurement of Uncertainty before 1900 , it seems to mostly cover new ground, or at least cover it differently M...A brief but truly excellent exploration of the fundamental ideas that make statistics a unique mathematical science, with clear and insightful examples The writing style is clear, concise and precise, with a sprinkling of wit artfully placed The author provides a historical perspective on how certain questions that seemed unanswerable were tackled in some very creative ways and led at times to counterintuitive answers Indeed, some so much that many people refuse to believe them In fact, I ca A brief but truly excellent exploration of the fundamental ideas that make statistics a unique mathematical science, with clear and insightful examples The writing style is clear, concise and precise, with a sprinkling of wit artfully placed The author provides a historical perspective on how certain questions that seemed unanswerable were tackled in some very creative ways and led at times ...An overview of the foundational concepts of modern statistics I liked the way the author organized the topics, but I wish he had taken less of an historical approach and wroteabout the pillars role in contemporary practice Still, as a text on...A brilliant book Clearly written and illuminating with insight, this sort of historical and philosophical inquiry into statistics ought to be written for every other academic discipline.A bit disappointing, want to hear good stories to gain practical wisdoms, instead read a bunch of history.Great book for statisticians and lovers of statistics Some fascinating stories about the development of statistical thought, and wonderful insights as well.Why Seven Stephen Stigler notes that the title of his Seven Pillars of Statistical Wisdom is borrowed from T.E Lawrence s own Seven Pillars of Wisdom , and that both he and Lawrence of Arabia drew on Proverbs 9 1 as a source Wisdom hath built her house, she hath hewn out her seven pillars 3 With this bow to tradition, Stigler goes on to note that an eighth pillar may well be forthcoming, without commenting on what it might be 203.While we await this possible eighth pillar, the seven c Why Seven Stephen Stigler notes that the title of his Seven Pillars of Statist...The book is about seven themes of statistics aggregation means mostly , likelihood n root rule and exceptions , intercomparison student t test , regression regression to the mean and its implications , design randomization and residual residual plots and nested models I m not sure who the audience is supposed to ...

17 May 2017

Stephen M. Stigler