Abstract: The book investigates the misapplication of conventional statistical techniques to fat tailed distributions and looks for remedies, when possible.
Switching from thin tailed to fat tailed distributions requires more than "changing the color of the dress". Traditional asymptotics deal mainly with either n=1 or $n=\infty$, and the real world is in between, under of the "laws of the medium numbers" --which vary widely across specific distributions. Both the law of large numbers and the generalized central limit mechanisms operate in highly idiosyncratic ways outside the standard Gaussian or Levy-Stable basins of convergence.
A few examples:
+ The sample mean is rarely in line with the population mean, with effect on "naive empiricism", but can be sometimes be estimated via parametric methods.
+ The "empirical distribution" is rarely empirical.
+ Parameter uncertainty has compounding effects on statistical metrics.
+ Dimension reduction (principal components) fails.
+ Inequality estimators (GINI or quantile contributions) are not additive and produce wrong results.
+ Many "biases" found in psychology become entirely rational under more sophisticated probability distributions
+ Most of the failures of financial economics, econometrics, and behavioral economics can be attributed to using the wrong distributions.
This book, the first volume of the Technical Incerto, weaves a narrative around published journal articles.
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构建之法（第三版）
邹欣 / 人民邮电出版社 / 2017-6 / 69.00元
软件工程牵涉的范围很广, 同时也是一般院校的同学反映比较空洞乏味的课程。 但是，软件工程 的技术对于投身 IT 产业的学生来说是非常重要的。作者有在世界一流软件企业 20 年的一线软件开 发经验，他在数所高校进行了多年的软件工程教学实践，总结出了在 16 周的时间内让同学们通过 “做 中学 (Learning By Doing)” 掌握实用的软件工程技术的教学计划，并得到高校师生的积极反馈。在此 ......一起来看看 《构建之法（第三版）》 这本书的介绍吧!
