R: Soil Compositions of Physical and Chemical Characteristics

Soils {car} | R Documentation

## 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.

[Package car version 2.1-4 Index]