In the article some parameters of quality of life of population of 80 Russian regions are examined. The main attention is paid to the difference between regions and variables, thus they are divided into groups according to the territorial characteristics and sense of variables. For analysis PCA (Principal Component Analysis) via singular value decomposition is used. There are tools that allow to analyze, track the dynamics of movement and identify the the weakest points for repeated observations in the form of size matrices n x p . Assume a set of data X-t,t =1, k . Generally, they can be investigated using time series analysis methods, but there are often cases of mutual correlation between variables, as well as various kinds of relations between objects of observation (geographical, regional, cultural, etc.). In order to level these restrictions or, conversely, to take into account the relationship between objects, it is proposed to use the method STATIS (Structuring Three-way data sets in Statistics) [1], [2] According to it, a common space is defined for the initial data set. By analyzing a common space, it is possible to track the evolution in time not only for statistical units, but also variables or their groups. Such a common space is called the compromise matrix.
