This paper illustrates the versatility of biplot methodology when
analysing multivariate data from diverse disciplines. The modern approach of
Gower & Hand (1996) whereby biplots are regarded as multivariate
analogues of ordinary scatter plots is utilised for extending biplot
methodology introducing several novel applications. Focus is on biplot
applications where the merits of principal component biplots and canonical
variate analysis biplots are illustrated with data sets from higher
education, the manufacturing industry, the mining industry, agriculture,
finance and archaeology. It is shown how to equip biplots with quality
regions, classification regions and acceptance regions; how α-bags
superimposed on biplots provide a quantification of the multidimensional
overlap of classes as well as enable biplots to be used with large data
sets; how to use biplots for exploring multi-dimensional reality and in
sophisticated classification procedures.