Talk:Systematic error

Random error
There's no page in Wikipedia that discusses this topic. There's a page wiht this title, but it redirects to errors and residuals in statistics, in which the word "random" is never used. I will start a stub that I won't be able to complete. But I think that a stub is better than the actual situation. Paolo.dL (talk) 18:00, 9 August 2008 (UTC)

an example?
"The Wall Street Journal (November 8, 1983, p. 37) reported on the Vancouver Stock Exchange, which created an index much like the Dow-Jones Index. It began with a nominal value of 1,000.000 and was recalculated after each recorded transaction by calculation to four decimal places, the last place being truncated so that three decimal places were reported. Truncating the fourth decimal of a number measured to approximately 10^3 might seem innocuous. Yet, within a few months the index had fallen to 520, while there was no general downturn in economic activity. The problem, of course, was insufficient attention given to the method of rounding. When recalculated properly, the index was found to be 1098.892 (Toronto Star, November 29, 1983)." -- B. D. McCullough and H. D. Vinod, "The Numerical Reliability of Econometric Software", Journal of Economic Literature, Vol. XXXVII (June 1999), pp. 633–665. Naaman Brown (talk) 18:18, 29 December 2011 (UTC)

Contribution of a systematic by a system of analysis
Airy's theory of errors (1861) defined the standard error as the root mean square error for a data sample. To get an accurate measure of this quantity one needs a large set of data to work. For small datasets one is more likely to get values near the distribution's peak and the use of Bessel's correction, n-1, in the formula for the standard deviation gives a better estimate. This may justify the exclusion of outliers from the data analysis but care is necessary in doing so. When working with measurements that fluctuate about a mean the formulas used to compute mean and standard deviation also contribute a little error to the estimates. The law of large numbers states that error for an average decreases as number of measurements increases. --Jbergquist (talk) 23:40, 11 December 2014 (UTC)