How we load our data sets with theories and why we do so purposefully.

Citation data:

Studies in history and philosophy of science, ISSN: 0039-3681, Vol: 60, Page: 1-6

Publication Year:
Usage 120
Downloads 73
Abstract Views 35
Link-outs 12
Captures 6
Readers 5
Exports-Saves 1
Social Media 9
Tweets 7
Shares, Likes & Comments 2
Repository URL:
Rochefort-Maranda, Guillaume
Elsevier BV
Arts and Humanities
Most Recent Tweet View All Tweets
article description
In this paper, I compare theory-laden perceptions with imputed data sets. The similarities between the two allow me to show how the phenomenon of theory-ladenness can manifest itself in statistical analyses. More importantly, elucidating the differences between them will allow me to broaden the focus of the existing literature on theory-ladenness and to introduce some much-needed nuances. The topic of statistical imputation has received no attention in philosophy of science. Yet, imputed data sets are very similar to theory-laden perceptions, and they are now an integral part of many scientific inferences. Unlike the existence of theory-laden perceptions, that of imputed data sets cannot be challenged or reduced to a manageable source of error. In fact, imputed data sets are created purposefully in order to improve the quality of our inferences. They do not undermine the possibility of scientific knowledge; on the contrary, they are epistemically desirable.