dat <- eden.potato
# 1925 qualitative
d5a <- subset(dat, year=='1925a')
desplot(trt~col*row, d5a, text=yield, cex=1, shorten='no')
anova(m5a <- aov(yield~trt+factor(row)+factor(col), d5a)) # table 2
# 1926 qualitative
d6a <- subset(dat, year=='1926a')
desplot(trt~col*row, d6a, text=yield, cex=1, shorten='no')
anova(m6a <- aov(yield~trt+factor(row)+factor(col), d6a)) # table 4
# 1925 quantitative
d5 <- subset(dat, year=='1925b')
desplot(yield ~ col*row, d5, out1=block, text=trt, cex=1)
# Trt 't' not defined, seems to be the same as 'a'
dotplot(trt~yield|block, d5)
anova(m5 <- aov(yield~trt+block, d5)) # table 6
# 1926 quantitative
d6 <- subset(dat, year=='1926b')
desplot(yield ~ col*row, d6, out1=block, text=trt, cex=1)
anova(m6 <- aov(yield~trt+block, d6)) # table 7
# 1927 qualitative + quantitative
d7 <- droplevels(subset(dat, year==1927))
desplot(yield ~ col*row, d7, out1=block, text=trt, cex=1, col=ptype)
# Table 8. Anova, mean yield tons / acre
anova(m7 <- aov(yield~trt+block+ptype + ptype:potash, d7))
require("reshape2")
me7 <- melt(d7, measure.vars='yield')
acast(me7, potash~nitro, fun=mean) * 40/2240 # English ton = 2240 lbs
acast(me7, potash~ptype, fun=mean) * 40/2240Run the code above in your browser using DataLab