Summary
The advantages and drawbacks of some graphical methods as interpreting aids for cooperative tests are demonstrated using results of slag sample analyses (5 laboratories, 7 components). In cases of low dimensions (components) the method of regular polygons has been found most informative. For higher dimensions modern data analysis techniques, such as principal components analysis (pca), correspondence analysis and discriminant analysis are to be preferred. From pca of correlation matrices one can also derive best choices of feature subsets to construct good polygons. The sensitivity of partial correlation coefficients due to deviating laboratory manners can be assessed by leaving-one-out comparisons.
Similar content being viewed by others
Literatur
Ahrens H, Läuter J (1981) Mehrdimensionale Varianzanalyse. Akademie-Verlag, Berlin
Doerffel K (1987) Statistik in der analytischen Chemie. VEB Deutscher Verlag für Grundstoffindustrie, Leipzig
Lebart L, Morineau A, Fénelon JP (1984) Statistische Datenanalyse. Akademie-Verlag, Berlin
Rechenberg W (1985) Fresenius Z Anal Chem 320:217–224
Zwanziger H (1986) 3. Diskussionstreffen der AG Chemometrik der Chemischen Gesellschaft der DDR, Leipzig
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Doerffel, K., Zwanziger, H. Zur multivariaten Auswertung von Ringversuchen. Z. Anal. Chem. 329, 1–6 (1987). https://doi.org/10.1007/BF00487531
Received:
Issue Date:
DOI: https://doi.org/10.1007/BF00487531