Soils
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.)
- Keywords
- datasets
Usage
Soils
Details
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 Block
),
by using either Group
or Gp
as the factor, or a two-way randomized block
design using Block
, Contour
and Depth
(quantitative, so orthogonal
polynomial contrasts are useful).
Format
A data frame with 48 observations on the following 14 variables. There are 3 factors and 9 response variables.
Group
a factor with 12 levels, corresponding to the combinations of
Contour
andDepth
Contour
a factor with 3 levels:
Depression
Slope
Top
Depth
a factor with 4 levels:
0-10
10-30
30-60
60-90
Gp
a factor with 12 levels, giving abbreviations for the groups:
D0
D1
D3
D6
S0
S1
S3
S6
T0
T1
T3
T6
Block
a factor with levels
1
2
3
4
pH
soil pH
N
total nitrogen in %
Dens
bulk density in gm/cm$^3$
P
total phosphorous in ppm
Ca
calcium in me/100 gm.
Mg
magnesium in me/100 gm.
K
phosphorous in me/100 gm.
Na
sodium in me/100 gm.
Conduc
conductivity
References
Khattree, R., and Naik, D. N. (2000) Multivariate Data Reduction and Discrimination with SAS Software. SAS Institute.
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), http://www.jstatsoft.org/v17/i06.