Soil Compositions of Physical and Chemical Characteristics
Soil characteristics were measured on samples from three types of
contours (Top, Slope, and Depression) and at four depths (0-10cm,
10-30cm, 30-60cm, and 60-90cm). The area was divided into 4
blocks, in a randomized block design. (Suggested by Michael Friendly.)
A data frame with 48 observations on the following 14 variables. There are 3 factors and 9 response variables.
a factor with 12 levels, corresponding to the combinations of
a factor with 3 levels:
a factor with 4 levels:
a factor with 12 levels, giving abbreviations for the groups:
a factor with levels
total nitrogen in %
bulk density in gm/cm$^3$
total phosphorous in ppm
calcium in me/100 gm.
magnesium in me/100 gm.
phosphorous in me/100 gm.
sodium in me/100 gm.
These data provide good examples of MANOVA and canonical discriminant analysis in a somewhat
complex multivariate setting. They may be treated as a one-way design (ignoring
by using either
Gp as the factor, or a two-way randomized block
Depth (quantitative, so orthogonal
polynomial contrasts are useful).
Horton, I. F.,Russell, J. S., and Moore, A. W. (1968)
Multivariate-covariance and canonical analysis:
A method for selecting the most effective discriminators in a multivariate situation.
Biometrics 24, 845–858.
Originally from http://www.stat.lsu.edu/faculty/moser/exst7037/soils.sas but no longer available there.
Khattree, R., and Naik, D. N. (2000)
Multivariate Data Reduction and Discrimination with SAS Software.
Friendly, M. (2006)
Data ellipses, HE plots and reduced-rank displays for
multivariate linear models: SAS software and examples.
Journal of Statistical Software, 17(6),
Dataset imported from https://www.r-project.org.