Comment on a Letter to the Editor by M. Rösslein, M. Wolf, B. Wampfler, and W. Wegscheider

The square root of the sample variance s2 is the standard deviation s. By use of Eq. 3a the variance of a population is estimated on the basis of n samples obtained randomly from the distribution. With increasing degrees of freedom, the skewness in the mean value for s will be reduced, because the distribution of s will approach a Normal distribution with increasing degrees of freedom. Because the formulas of distribution functions are difficult to interpret, a graphical representation of the sampling distribution f(s) is given in Fig. 1, for arbitrarily chosen s0 = 5. [...]the experimental data are used to estimate parametric models where the parameters are often physically meaningful quantities. [...]the χ2 distribution is also of interest in metrology. With increasing degree of freedom, Student’s t distribution approaches a Normal distribution, and the differences between these distributions become negligible for 30 degrees of freedom. [...]the limits enclosing a certain area under the curve (symmetric to zero) are wider compared with a Normal distribution the smaller the number of degrees of freedom.