## Soil Compositions of Physical and Chemical Characteristics

### Description

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.)

### Usage

Soils

### 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`

and `Depth`

`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

### 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).

### Source

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.

### 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.