cochran.factorial {agridat} | R Documentation

## Factorial experiment in beans

### Description

Factorial experiment in beans

### Usage

    data("cochran.factorial")

### Format

A data frame with 32 observations on the following 4 variables.

`rep`

  rep factor

`block`

  block factor

`trt`

  treatment factor, 16 levels

`yield`

  yield (pounds)

### Details

Conducted by Rothamsted Experiment Station in 1936. The treatments are listed below.

d = dung: None, 10 tons/acre.

n = nitrochalk: None, 0.4 hundredweight nitrogen per acre.

p = Superphosphate: None, 0.6 hundredweight per acre

k = muriate of potash: None, 1 hundredweight K20 per acres.

The response variable is the yield of beans.

### Source

Cochran, W.G. and Cox, G.M. (1957), Experimental Designs, 2nd ed., Wiley and Sons, New York, p. 160.

### Examples

    data(cochran.factorial)
    dat <- cochran.factorial

    # Split treatment into individual factors
    dat <- transform(dat,
                     d = -1 + 2 * grepl('d',trt),
                     n = -1 + 2 * grepl('n',trt),
                     p = -1 + 2 * grepl('p',trt),
                     k = -1 + 2 * grepl('k',trt))
    dat <- transform(dat, d=factor(d), n=factor(n), p=factor(p), k=factor(k))

    # Cochran table 6.5.
    m1 <- lm(yield ~ rep * block + (d+n+p+k)^3, data=dat)
    anova(m1)

    if(require(FrF2)){
      aliases(m1)
      MEPlot(m1, select=3:6,
             main="cochran.factorial - main effects plot")
    }

[Package agridat version 1.16 Index]