(Vole Data)- Consider the “microtus” dataset in the “Flury”
library in R.
The sample consists of 288 specimens collected mostly in
Central Europe (Alps and Jura mountains) and in Toscana. One
peculiar aspect of this data set is that the chromosomes of 89
specimens were analyzed to identify the species. Only the
morphometric characteristics are available for the remaining 199
specimens…â€
#The following dataset can be accessed in R using:
install.packages(“Flury”); library(Flury); data(“microtus”)
head(microtus)
Group M1Left M2Left M3Left Foramen Pbone Length Height
Rostrum
1 multiplex 2078 1649 1708 3868 5463 2355 805 475
2 multiplex 1929 1551 1550 3825 4741 2305 760 450
3 multiplex 1888 1613 1674 4440 4807 2388 775 460
4 multiplex 2020 1670 1829 3800 4974 2370 766 460
5 multiplex 2223 1814 1933 4222 5460 2470 815 475
6 multiplex 2190 1800 2066 4662 4860 2535 838 521
Thus, the GROUP variable contains information for 89
observations only while the remaining 199 observations need to be
classified.
Q1) What would be the appropriate exploratory data
analysis for this kind of a dataset?
Q2) What model(s) should be considered for predicting
the remaining 199 observations?
