Мастер wrote:tubeswell wrote:But my earlier proposition to take several (systematically random) sample sets of measurements, and then analyse the variance between the samples could give more confidence about the mean and SD in the statistics, and thus by inference in the population - could it not?
Assuming that each observation is an independent draw (probably reasonable, as long as I'm not changing the process or any equipment used isn't slowly wearing out), then I could estimate the mean of the population (which in this case would be the distribution of draws from this observational process) quite accurately with enough draws. The standard error of the mean would go down at the rate of the square root of the number of observations.
But that would then tell me the mean value of a measurement made by this process. Whether the mean of a measurement by this method is equal to the actual distance or not is another question. If the method produces unbiased results (there are errors, but the "average" error is zero), then it would. If the errors are biased (i.e., on average, they are not equal to zero), then such a procedure wouldn't tell us that.
Yes but I initially thought you were only interested in an estimate of the distance. Any measurement is subject to the calibration of the measuring equipment - that is why I suggested factoring in variables such as whiskey - to help with the calibration of your vertical angle measurement.