When Evidence is Not in the Mean
Marcel J. Boumans
University of Amsterdam; Tinbergen Institute; Erasmus University Rotterdam (EUR) - Erasmus Institute for Philosophy and Economics (EIPE)
July 14, 2009
Centre for Philosophy of Natural and Social Science (CPNSS) Discussion Paper Series DP 76/05
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.
Number of Pages in PDF File: 31
Keywords: measurement, accuracy, precision, method of least squares
JEL Classification: B4working papers series
Date posted: July 17, 2009
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