Veronika R. Meyer | Authors

Spreadsheet computer simulations can identify the influencing factors for the set-up of a calibration function such as the number of calibration points and their distribution or the position of the experimental points. By using a Monte Carlo approach, the quality of the experimental results (bias and standard deviation) can be studied under different conditions. This article presents a spreadsheet for the simulation of unweighted and weighted linear least-squares fit.

The statistical nature of experiments leads to the fact that standard deviation (SD) of replicate analysis is not constant but a number with some variability: a standard deviation has its own standard deviation. As a consequence, a SD calculated from three experiments is not rugged and even SDs from ten experiments show a great variability. Analysts should be aware that with 100 or more the results have low scatter

Guest author Veronika Meyer provides tips for decreasing measurement uncertainty caused by sample preparation.