Looking at quantitative biological data through scatter diagrams

Pierre Jolicoeur
Additional contact information
Pierre Jolicoeur: University of Montreal, Department of Biological Science

Chapter Chapter 1 in Introduction to Biometry, 1999, pp 3-5 from Springer

Abstract: Abstract In applied statistics in general, and in biometry in particular, graphical representations and numerical techniques are complementary and often equally important. One of the most useful graphical methods in statistics is the scatter diagram, in which variable measurements are represented simply by dots dispersed on a surface overlaid by Cartesian coordinate axes (named after the French mathematician René Descartes, 1596–1650). Such coordinate axes are usually perpendicular to each other. While a scatter diagram may have a single coordinate axis (one-dimensional dispersion) or more than two coordinate axes (three-dimensional or multidimensional dispersion), the most commonly used version is the bivariate scatter diagram, which contains two coordinate axes (two-dimensional dispersion) and where dots represent pairs of measurements (see figures 1.2.1 and 1.2.2).

Keywords: Scatter Diagram; Bilateral Symmetry; Radial Symmetry; Human Skeleton; Graphical Examination (search for similar items in EconPapers)
Date: 1999
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4615-4777-8_2

Ordering information: This item can be ordered from
http://www.springer.com/9781461547778

DOI: 10.1007/978-1-4615-4777-8_2

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().