When Evidence is Not in the Mean

Centre for Philosophy of Natural and Social Science (CPNSS) Discussion Paper Series DP 76/05

31 Pages Posted: 17 Jul 2009  

Marcel J. Boumans

Utrecht University School of Economics

Date Written: July 14, 2009

Abstract

When observing or measuring phenomena, errors are inevitable, one can only aspire to reduce these errors as much as possible. An obvious strategy to achieve this reduction is by using more precise instruments. Another strategy was to develop a theory of these errors that could indicate how to take them into account. One of the greatest achievements of statistics in the beginning of the 19th century was such a theory of error. This theory told the practitioners that the best thing they could do is taking the arithmetical mean of their observations. This average would give them the most accurate estimate of the value they were searching for. Soon after its invention, this method made a triumphal march across various sciences. However, not in all sciences one stood waving aside. This method, namely, only worked well when the various observations were made under similar circumstances and when there were very many of them. And this was not the case for e.g. meteorology and actuarial science, the two sciences discussed in this paper.

Keywords: measurement, accuracy, precision, method of least squares

JEL Classification: B4

Suggested Citation

Boumans, Marcel J., When Evidence is Not in the Mean (July 14, 2009). Centre for Philosophy of Natural and Social Science (CPNSS) Discussion Paper Series DP 76/05. Available at SSRN: https://ssrn.com/abstract=1433778 or http://dx.doi.org/10.2139/ssrn.1433778

Marcel J. Boumans (Contact Author)

Utrecht University School of Economics ( email )

Kriekenpitplein 21-22
Adam Smith Building
Utrecht, +31 30 253 7373 3584 EC
Netherlands
+31 30 253 6287 (Phone)

HOME PAGE: http://www.uu.nl/leg/staff/MJBoumans

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