The board stiffness dataset is available in the ACSWR package through the stiff data.frame stiff. The dataset consists of four measures of stiffness for 30 boards. The first measure of stiffness is obtained by sending a shock wave down the board, the second measure is obtained by vibrating the board, and the remaining two are obtained from static tests. A quick method of identifying the outliers in a multivariate dataset is by using the Mahalanobis distance function. The further the distance an observation is from the center, the more likely it is that the observation will be an outlier:

> data(stiff)
> sort(mahalanobis(stiff,colMeans(stiff),cov(stiff)),decreasing = TRUE)
 [1] 16.8474070168 12.2647549939  9.8980384087  7.6166439053
 [5]  6.2837628235  5.4770195915  5.2076098038  5.0557446013
 [9]  4.9883497928  4.5767867224  3.9900602512  3.5018290410
[13]  3.3979804418  2.9951752177  2.6959023813  2.5838186338
[17]  2.5385575365  2.3816049840  2.2191408683  1.9307771418
[21]  1.4876569689  1.4649908273  1.3980776252  1.3632123553
[25]  1.0792484215  0.7962095966  0.7665399704  0.6000128595
[29]  0.4635158597  0.1295713581