Why distinguish between statistics and mathematical statistics - the case of Swedish academia

Georg Lindgren, Peter Guttorp

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A separation between the academic subjects statistics and mathematical statistics has existed in Sweden almost as long as there have been statistics professors. The same distinction has not been maintained in other countries. Why is it kept in Sweden?

In May 2015 it has been 100 years since Mathematical Statistics was formally established as an academic discipline at a Swedish university where Statistics had existed since the turn of the century.

We give an account of the debate in Lund and elsewhere about this division during the first decades after 1900 and present two of its leading personalities. The Lund University astronomer (and mathematical statistician) C.V.L. Charlier was a leading proponent for a position in mathematical statistics at the university. Charlier's adversary in the debate was Pontus Fahlbeck, professor in political science and statistics, who reserved the word statistics for ``statistics as a social science''. Charlier not only secured the first academic position in Sweden in mathematical statistics for his former Ph.D. student Sven Wicksell, but he also demonstrated that a mathematical statistician can be influential in matters of state, finance, as well as in different natural sciences. Fahlbeck saw mathematical statistics as a set of tools that sometimes could be useful in his brand of statistics.

After a summary of the organisational growth of the statistical sciences in Sweden that has taken place during the last 50 years, we discuss what effects the Charlier-Fahlbeck divergence might have had on this development.
Original languageEnglish
PublisherMathematical Statistics, Centre for Mathematical Sciences, Lund University
Number of pages19
Publication statusPublished - 2016 Aug 15

Publication series

NamePreprints in Mathematical Sciences
PublisherCentre for Mathematical Sciences
ISSN (Print)1403-9338

Subject classification (UKÄ)

  • Social Sciences
  • Probability Theory and Statistics


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