by Paul Rosenbaum’s latest book — Observation and experiment: an introduction to causal inference — is a well-written introduction to some of the most important and far-reaching ideas in modern statistics. With only a minimum of mathematics, the author manages to give a lively and interesting account of how statisticians try to use statistics to make causal inferences from observational studies and experiments. For non-graduate social science students with no or little ‘technical’ background, this is highly recommended reading. Especially for those who want to get their first grip on the nowadays so influential ‘potential outcomes’ paradigm, this is probably the most accessible presentation available. A must-read. That said, there are, of course, critiques that can be waged
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Lars Pålsson Syll considers the following as important: Statistics & Econometrics
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Paul Rosenbaum’s latest book — Observation and experiment: an introduction to causal inference — is a well-written introduction to some of the most important and far-reaching ideas in modern statistics. With only a minimum of mathematics, the author manages to give a lively and interesting account of how statisticians try to use statistics to make causal inferences from observational studies and experiments. For non-graduate social science students with no or little ‘technical’ background, this is highly recommended reading. Especially for those who want to get their first grip on the nowadays so influential ‘potential outcomes’ paradigm, this is probably the most accessible presentation available. A must-read. That said, there are, of course, critiques that can be waged against that paradigm. But I save that for another post.