Cause and Correlation in Biology: A User's Guide to Path by Bill Shipley

By Bill Shipley

This publication is going past the truism that 'correlation doesn't suggest causation' and explores the logical and methodological relationships among correlation and causation. It provides a chain of statistical tools that may try out, and probably detect, cause-effect relationships among variables in events during which it isn't attainable to behavior randomised or experimentally managed experiments. a lot of those tools are really new and so much are commonly unknown to biologists. as well as describing tips to behavior those statistical assessments, the ebook additionally places the equipment into historic context and explains after they can and can't justifiably be used to check or notice causal claims. Written in a conversational sort that minimises technical jargon, the publication is aimed toward training biologists and complex scholars, and assumes just a very easy wisdom of introductory statistics.

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