forum 9: week of 12 March: Fisher and the design of experiments

Edward, I agree with you to some degree on questioning why we (scientists, philosophers of science) are obsessed with causes. While the idea of causation has been around for a long time, the idea of correlation representing causation has not been around for that long! Karl Pearson insisted that correlation is fundamental to science, and that correlation is to replace causation. Hence, the idea about causation being a special form of correlation was driven primarily by Karl Pearson in the (late 19th)/(early 20th) century. From my (limited) exposure to studying the history of statistics, it seems that Pearson's argument about correlation being fundamental to science has gone out of hand, with numerous scientists not using the concept properly and almost always misinterpreting the inference from observed correlation. In other words, Pearson presented his argument for correlation replacing causation, then many scientists have been misguided in their use of Pearson's correlation coefficient as thinking that statements of causation are the norm (or de facto standard) when inferring correlations. I say that they (scientists) have been (and still are) misguided because that's what Pearson taught them, yet no one has questioned the grounds for inferring those causal statements from correlations until much later (e.g., since Nancy Cartwright came along in the 1980s)! Even though I am unable to (fully) answer your question, I hope that I have been able to shed light on the issue in an effective manner. I am able to give insight to this question, even though it is not really related to the reading on Fisher, because of my research interests in (probabilistic) causal inference. Yes, causal inference is a whole separate topic in itself, distinct from design and analysis of experiments! I hope that everyone can see by now that there are several sub-fields within the domain of statistics as a discipline. There's so much work to be done in accounting for the philosophical issues surrounding statistical techniques, it's not even funny!