PQStat - Baza Wiedzy

When we have decided how many principal components we need we can start generating them. In the case of principal components created on the basis of a correlation matrix they are computed as a linear combination of standardized original values. If, however, principal components have been created on the basis of a covariance matrix, they are computed as a linear combination of eigenvalues which have been centralized with respect to the mean of the original values.

The obtained principal components constitute new variables with certain advantages. First of all, the variables are not collinear. Usually there are fewer of them than original variables, sometimes much fewer, and they carry the same or a slightly smaller amount of information than the original values. Thus, the variables can easily be used in most multidimensional analyses.