You want to summarize your data with the standard error of the mean and/or confidence intervals.

Getting the standard error of the mean involves two steps: first get the standard deviation and count for each group, then use those values to calculate the standard error. The standard error for each group is just the standard deviation divided by the square root of the sample size:

library(MASS) # For the data set
library(plyr)

ca <- ddply(cabbages, c("Cult", "Date"), summarise,
      Weight = mean(HeadWt, na.rm=TRUE),
      sd = sd(HeadWt, na.rm=TRUE),
      n = sum(!is.na(HeadWt)),
      se = sd/sqrt(n))

ca

 Cult Date Weight        sd  n         se
  c39  d16   3.18 0.9566144 10 0.30250803
  c39  d20   2.80 0.2788867 10 0.08819171
  c39  d21   2.74 0.9834181 10 0.31098410
  c52  d16   2.26 0.4452215 10 0.14079141
  c52  d20   3.11 0.7908505 10 0.25008887
  c52  d21   1.47 0.2110819 10 0.06674995