gregory.cotton: Factorial experiment of cotton in Sudan.

Description

Factorial experiment of cotton in Sudan.

Usage

data("gregory.cotton")

Arguments

Format

A data frame with 144 observations on the following 6 variables.

yield: a numeric vector
year: year
nitrogen: nitrogen level
date: sowing date
water: irrigation amount
spacing: spacing between plants

Details

Experiment conducted in Sudan at the Gezira Research Farm in 1929-1930 and 1930-1931. The effects on yield of four factors was studied in all possible combinations.

Sowing dates in 1929: D1 = Jul 24, D2 = Aug 11, D3 = Sep 2, D4 = Sep 25.

Spacing: S1 = 25 cm between holes, S2 = 50 cm, S3 = 75 cm. The usual spacing is 50-70 cm.

Irrigation: I1 = Light, I2 = Medium, I3 = Heavy.

Nitrogen: N0 = None/Control, N1 = 600 rotls/feddan.

In each year there were 4*3*2*2=72 treatments, each replicated four times. The means are given here.

Gregory (1932) has two interesting graphics: 1. radial bar plot 2. photographs of 3D model of treatment means.

References

Paterson, D. Statistical Technique in Agricultural Research, p. 211.

Examples

Run this code

# NOT RUN {
data(gregory.cotton)
dat <- gregory.cotton

if(require(dplyr)){
  # Main effect means, Gregory table 2
  dat 
# }
# NOT RUN {
<!-- %>% group_by(year,date) %>% summarise(yield=mean(yield)) -->
# }
# NOT RUN {
  dat 
# }
# NOT RUN {
<!-- %>% group_by(year,spacing) %>% summarise(yield=mean(yield)) -->
# }
# NOT RUN {
  dat 
# }
# NOT RUN {
<!-- %>% group_by(year,water) %>% summarise(yield=mean(yield)) -->
# }
# NOT RUN {
  dat 
# }
# NOT RUN {
<!-- %>% group_by(year,nitrogen) %>% summarise(yield=mean(yield)) -->
# }
# NOT RUN {
}

# Figure 2 of Gregory. Not recommended, but an interesting exercise.
# http://stackoverflow.com/questions/13887365
if(require(ggplot2)){
  d1 <- subset(dat, year=="Y1")
  d1 <- transform(d1, grp=factor(paste(date,nitrogen,water,spacing)))
  d1 <- d1[order(d1$grp),] # for angles
  # Rotate labels on the left half 180 deg. First 18, last 18 labels
  d1$ang <- 90+seq(from=(360/nrow(d1))/1.5, to=(1.5*(360/nrow(d1)))-360,
                   length.out=nrow(d1))+80
  d1$ang[1:18] <- d1$ang[1:18] + 180
  d1$ang[55:72] <- d1$ang[55:72] + 180
  # Lables on left half to right-adjusted
  d1$hjust <- 0
  d1$hjust[1:18] <- d1$hjust[55:72] <- 1
  
  gg <- ggplot(d1, aes(x=grp,y=yield,fill=factor(spacing))) +
    geom_col() +
    guides(fill=FALSE) + # no legend for 'spacing'
    coord_polar(start=-pi/2) + # default is to start at top
    labs(title="gregory.cotton 1929",x="",y="",label="") +
    # The bar columns are centered on 1:72, subtract 0.5 to add radial axes
    geom_vline(xintercept = seq(1, 72, by=3)-0.5, color="gray", size=.25) +
    geom_vline(xintercept = seq(1, 72, by=18)-0.5, size=1) +
    geom_vline(xintercept = seq(1, 72, by=9)-0.5, size=.5) +
    geom_hline(yintercept=c(1,2,3)) + 
    geom_text(data=d1, aes(x=grp, y=max(yield), label=grp, angle=ang, hjust=hjust),
              size=2) +
    theme(panel.background=element_blank(),
          axis.title=element_blank(),
          panel.grid=element_blank(),
          axis.text.x=element_blank(),
          axis.text.y=element_blank(),
          axis.ticks=element_blank() )
  print(gg)
  
}

# }

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