robustbase (version 0.93-5)

cushny: Cushny and Peebles Prolongation of Sleep Data

Description

The original data set was bivariate and recorded for ten subjects the prolongation of sleep caused by two different drugs. These data were used by Student as the first illustration of the paired t-test which only needs the differences of the two measurements. These differences are the values of cushny.

Usage

data(cushny, package="robustbase")

Format

numeric vector, sorted increasingly: 0 0.8 1 1.2 1.3 1.3 1.4 1.8 2.4 4.6

References

Student (1908) The probable error of a mean. Biometrika 6, 1--25.

Fisher, R.A. (1925) Statistical Methods for Research Workers; Oliver & Boyd, Edinburgh.

Anderson, T.W. (1958) An Introduction to Multivariate Statistical Analysis; Wiley, N.Y.

Hampel, F., Ronchetti, E., Rousseeuw, P. and Stahel, W. (1986) Robust Statistics: The Approach Based on Influence Functions; Wiley, N.Y.

Examples

# NOT RUN {
data(cushny)

plot(cushny,  rep(0, 10), pch = 3, cex = 3,
     ylab = "", yaxt = "n")
plot(jitter(cushny),  rep(0, 10), pch = 3, cex = 2,
     main = "'cushny' data (n= 10)", ylab = "", yaxt = "n")
abline(h=0, col="gray", lty=3)
myPt <- function(m, lwd = 2, ..., e = 1.5*par("cxy")[2])
  segments(m, +e, m, -e, lwd = lwd, ...)
myPt(  mean(cushny), col = "pink3")
myPt(median(cushny), col = "light blue")
legend("topright", c("mean", "median"), lwd = 2,
       col = c("pink3", "light blue"), inset = .01)

## The 'sleep' data from the standard 'datasets' package:
d.sleep <- local({ gr <- with(datasets::sleep, split(extra, group))
                   gr[[2]] - gr[[1]] })
stopifnot(all.equal(cushny,
                    sort(d.sleep), tolerance=1e-15))
# }