Graphics Reference
In-Depth Information
Introduction
4.1
Many papers refer to Tukey's (
) treatise on exploratory data analysis as the con-
tribution that transformed statistical thinking. In actual fact, new ideas introduced
by Tukey prompted many statisticians to give a more prominent role to data visual-
ization and more generally to data. However, J.W. Tukey in
had already begun
his daring provocation when at the annual meeting of the Institute of Mathematical
Statistics he gave his talk entitled “he Future of Data Analysis” (Tukey,
).
At the same time, the Frenchstatistician J.P.Benzécri brought his paradigm tothe
attention of the international scientific community in his paper“L'Analyse des Don-
nées” (Benzécri,
). As with Tukey's ideas, it appeared totally revolutionary with
respect to the “classical” statistical approaches for two reasons: i)theabsenceofany
apriorimodel and ii) the prominent role of graphical visualization in the analysis
of output. Unfortunately most of Benzécri's papers were written in French. Michael
Greenacre, in the preface to his well-known book heory and Application of Corre-
spondence Analysis (Greenacre,
), wrote: “In
I was invited to give a paper
on correspondence analysis at an international conference on multidimensional graph-
ical methods called Looking at Multivariate Data' in She
eld, England. [here] ...
I realized the tremendous communication gap between Benzécri's group and the Anglo-
American statistical school.”
hese simultaneous and independent stimuli for statistical analysis mainly based
on visualization did not occur by chance but as a consequence of extraordinary de-
velopments in information technology. In particular, technological innovations in
computer architecture permitted the storage of ever larger volumes of data and al-
lowed one to obtain even higher-quality graphical visualization (on screen and pa-
per).hesetwoelementscontributed togiving aprominentroletodata visualization.
he growth of data volume, on the other hand, determined the need for preliminary
(exploratory) analyses; graphical methods quickly proved their potential in this kind
of analysis. heperformance of graphics cards permitted one toobtain more detailed
visualization, and the developments in dynamic and
-D graphics have opened new
frontiers.
Aposterioriwecan state that at that time statisticians became conscious of the po-
tential of graphical visualization andof the need forexploratory analysis. However,it
appearsquitestrange thatthesetwo giantsofthestatistics world,TukeyandBenzécri,
are very rarely mentioned together in data analysis papers. heir common starting
point was the central role of data in statistical analysis; both of them were strong
believers that, in the future, the amount of available data would increase tremen-
dously, although the current abundance of data might be more than even they ex-
pected!
In light of this historical background, the title of the present contribution should
appear more clear to the reader. Our idea is to present visualization in the mod-
ern computer age following the precepts of data analysis theorists. Moreover, note
that the basic principles of data analysis are inspired by the elementary notions of
geometry.
