Veronika R. Meyer | Authors


Weighted Linear Least-Squares Fit — A Need? Monte Carlo Simulation Gives the Answer

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.

Can We Trust Experimental Standard Deviations?

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

Minimizing the Effect of Sample Preparation on Measurement Uncertainty

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