A new online computer program (BiDASys) for ordinary and uncertainty weighted least-squares linear regressions: case studies from food chemistry
A new computer program BiDASys (Bivariate Data Analysis System) is presented for the application of Ordinary and Uncertainty weighted least-squares linear regression models (OLR and UWLR) to experimental data from food chemistry. BiDASys has the following novel aspects: the statistical capability of detecting discordant outliers in bivariate data; new simulated critical values generated through our Monte Carlo simulation procedure for the probability of no-correlation in multivariate samples of sizes n=5–1000; and the only available software that can successfully achieve the application of the new UWLR model to the experimental data. The use of BiDASys is illustrated through three case studies from Glera-Prosecco (Italy), Quebec (Canada), and Tuscany to Basilicata (Italy), which confirms that the Sr isotopic ratio (87Sr/86Sr) can be used to track the geographical origin of wine (grapes plantation) and one more case study concerning the organochlorine pesticide levels in breast milk from Guerrero (Mexico).
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.