About the book
David Freedman sets out what readers need in order to follow empirical research papers in health and social science and to build statistical models of their own. Published studies anchor the discussion and many of the exercises, and the journal articles in question appear in full at the back. Freedman appraises the methods these studies use, along with other examples, illustrating both the principles of modeling and its pitfalls. Among the critical issues it raises is whether a model actually connects to the real phenomenon it is meant to describe. Freedman wrote it for statistics students at the advanced undergraduate and early graduate level, and for students and practitioners working in social science and health research.
Nassim Nicholas Taleb, who says he spent his career on the errors of statistics, praised its clarity and its use of real situations to show where statistical models reach their limits.
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This book has 1 recommendation
Nassim Nicholas Taleb (Flaneur)
I spent my life focusing on the errors of statistics and how they sometimes fail us in real life, because of the misinterpretation of what the techniques can do for you. This book is outstanding in the following two aspects: 1) It is of immense clarity, embedding everything in real situations, 2) It uses the real-life situation to critique the statistical model and show you the limit of statistic. For instance, he shows a few anecdotes here and there to illustrate how correlation between two variables might not mean anything causal, or how asymptotic properties may not be relevant in real life.
This is the first statistics book I've seen that cares about presenting statistics as a tool to GET TO THE TRUTH.
Please buy it.
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