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The Seven Pillars of Statistical Wisdom
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Stephen M. Stigler
Language:
English
Published/Copyright:
2016
About this book
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 and one which often seems counterintuitive. His original account will fascinate the interested layperson and engage the professional statistician.
Author / Editor information
Stigler Stephen M. :
Stephen M. Stigler is Ernest DeWitt Burton Distinguished Service Professor in the Department of Statistics at the University of Chicago.
Reviews
The hardest kind of scientific thinking concerns what’s in a field’s basement—and Stigler has brought a bright flashlight to his subterranean investigations of the ever-more-influential field of statistics.
-- Bradley Efron, Stanford University
-- Bradley Efron, Stanford University
Distilled from centuries of statistical research and garnished with wit, this masterfully prepared seven-course food for thought is a real treat for anyone who wants to reason with data, big or small.
-- Xiao-Li Meng, Harvard University
-- Xiao-Li Meng, Harvard University
Statistics has a core set of ideas that touch every aspect of our lives. Stigler has tapped into these and brought them to life.
-- Persi Diaconis, Stanford University
-- Persi Diaconis, Stanford University
This lively account of a radically counter-intuitive past at least encourages us to question big data’s reputation. Never entrust measurement to a monarch—or judgment to a computer.
-- Jonathon Keats New Scientist
-- Jonathon Keats New Scientist
Wonderful…Each of the seven pillars that Stigler, in his wisdom, has hewn from the past two centuries of statistical thought provides surprising insights.
-- Howard Wainer Science
-- Howard Wainer Science
Learning to reason statistically helps to make one a clearer and more logical thinker about important issues in the world. Part of the achievement of this book is that it makes some of this available to the general reader without the necessity of having to delve into more technical aspects of the subject.
-- Michael J. Evans Mathematical Reviews (starred review)
-- Michael J. Evans Mathematical Reviews (starred review)
Topics
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vii |
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1 |
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From Tables and Means to Least Squares Requires Authentication Unlicensed Licensed |
13 |
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Its Measurement and Rate of Change Requires Authentication Unlicensed Licensed |
45 |
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Calibration on a Probability Scale Requires Authentication Unlicensed Licensed |
63 |
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Within- Sample Variation as a Standard Requires Authentication Unlicensed Licensed |
87 |
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Multivariate Analysis, Bayesian Inference, and Causal Inference Requires Authentication Unlicensed Licensed |
107 |
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Experimental Planning and the Role of Randomization Requires Authentication Unlicensed Licensed |
149 |
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Scientific Logic, Model Comparison, and Diagnostic Display Requires Authentication Unlicensed Licensed |
171 |
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195 |
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205 |
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211 |
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225 |
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227 |
Publishing information
Pages and Images/Illustrations in book
eBook published on:
March 7, 2016
eBook ISBN:
9780674970199
Pages and Images/Illustrations in book
Main content:
240
Other:
9 halftones, 51 line illustrations, 2 tables
eBook ISBN:
9780674970199
Keywords for this book
how to read data; introduction to statistics; misleading data; limitations; correlation v causation; computation; significance test; analysis of variance; least squares; standard deviation; random distribution; multivariate analysis; quantitative; models; population
Audience(s) for this book
College/higher education;Professional and scholarly;
