Multivariate Data Analysis
Computer Practical 1
This computer practical can be accessed via the course web page:
It may be helpful to have the course web page, the course notes, and
this practical page all open in different tabs of your web browser
during this practical session. In particular, it may save time to
copy-and-paste R commands rather than re-typing them.
- First log in and start R in the usual way: Start -> All
Programs -> Statistical Software -> R -> R-2.15.1
- This practical is concerned with analysing data from the R package
ElemStatLearn. First ensure that the package is installed and
loaded. Type require(ElemStatLearn) to ensure the package is
loaded. If this doesn't give an error, everything is fine. In the
unlikely event that the command gives an error, you can install the package
using install.packages("ElemStatLearn") and then try again.
Do not re-install the package unless there is a problem. In particular, the package should work fine in the cluster room where the practical takes place.
- Work through all of the R code relating to the
ElemStatLearn examples, from the course notes, starting on page
6, all the way through to page 22 (inclusive). Do not just blindly enter
commands without thinking about what is going on. Make sure you
understand exactly what each command is doing. Use ?command to
get help on any command you are unsure about. If it still doesn't make
- For the zip.train data, produce separate variance matrix
image plots for each of the digits "0" through "9". Can you explain the
differences between the images, in relation to the digits they
- Consider the galaxy data set.
- What is the sample mean vector for the subset of the data
corresponding to an angle of 111?
- What is the covariance between radial.position and
velocity for the data subset referred to above?
- Consider the first 3 genes in the nci data set.
- What is the mean vector for the 3 genes?
- What is the sample variance matrix for the 3 genes?
- Use R to construct the centering matrix H6. Use R
to verify that it is idempotent.
There is nothing to hand in for this practical session. However, the
material covered in the first two practicals is necessary for
completion of the first project to be handed out in Week 5.