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Table of Contents Appendix Exercises Similar Mineral Waters | |
See also: survey of exercises, missing values, cluster analysis |
A problem often encountered in data analysis is finding the most similar observations in a set of data. There are several ways to uncover similarity between individual data sets. You can either use algorithms of cluster analysis, or rely on visual inspection by using principal component analysis to look at the high-dimensional data set. Using the correlation table may be misleading, since the correlation does not reflect absolute values.
Use the data set MINWATER
to find
(1) the two most similar brands of mineral water in the data set,
(2) the brand which is most similar to "Gasteiner", and
(3) the two most dissimilar brands.
Do you have an idea what to do with the missing values?
You can now go directly to the in
order to experiment with the data.
Last Update: 2006-Jän-18