Tuesday , November 5 2024
Home / Lars P. Syll / Confusing statistics and research

Confusing statistics and research

Summary:
Confusing statistics and research Coupled with downright incompetence in statistics, we often find the syndrome that I have come to call statisticism: the notion that computing is synonymous with doing research, the naïve faith that statistics is a complete or sufficient basis for scientific methodology, the superstition that statistical formulas exist for evaluating such things as the relative merits of different substantive theories or the “importance” of  the causes of a “dependent variable”; and the delusion that decomposing the covariations of some arbitrary and haphazardly assembled collection of variables can somehow justify not only a “causal model” but also, praise a mark, a “measurement model.” There would be no point in deploring such caricatures of the scientific enterprise if there were a clearly identifiable sector of social science research wherein such fallacies were clearly recognized and emphatically out of bounds.

Topics:
Lars Pålsson Syll considers the following as important:

This could be interesting, too:

Jodi Beggs writes Economists Do It With Models 1970-01-01 00:00:00

John Quiggin writes Monday Message Board

Mike Norman writes 24 per cent annual interest on time deposits: St Petersburg Travel Notes, installment three — Gilbert Doctorow

Lars Pålsson Syll writes Daniel Waldenströms rappakalja om ojämlikheten

Confusing statistics and research

Confusing statistics and researchCoupled with downright incompetence in statistics, we often find the syndrome that I have come to call statisticism: the notion that computing is synonymous with doing research, the naïve faith that statistics is a complete or sufficient basis for scientific methodology, the superstition that statistical formulas exist for evaluating such things as the relative merits of different substantive theories or the “importance” of  the causes of a “dependent variable”; and the delusion that decomposing the covariations of some arbitrary and haphazardly assembled collection of variables can somehow justify not only a “causal model” but also, praise a mark, a “measurement model.” There would be no point in deploring such caricatures of the scientific enterprise if there were a clearly identifiable sector of social science research wherein such fallacies were clearly recognized and emphatically out of bounds.

Dudley Duncan

Lars Pålsson Syll
Professor at Malmö University. Primary research interest - the philosophy, history and methodology of economics.

Leave a Reply

Your email address will not be published. Required fields are marked *