Culture&Territories#3

Neighbourhood & City
From the original set of 18 indicators two were removed: percentage of inhabited
dwellings with dirt floor (STA2_%_VPH_PT) and percentage of inhabited dwellings
without any material good (PTA1_%_VPH_NB) due to the null relation with
the phenomena and their unconstructive influence in the significance tests. For the
remaining sixteen indicators in the MQOLI, the KMO test turned out to be 0.843,
which indicates that the ACP presents a meritorious 2 adaptation to the structure of
the data. The BST was also considered, the value obtained (0.000) stands for perfect
significance ergo the null hypothesis (H0) can be rejected (that the variables
under study are independent). In conclusion the factorial analysis of the ACP is
appropriate 3 . The sedimentation graph in Fig. 3, which is used as a graphic contrast
to know the number of components to be conserved 4 , shows the relevance of using
only the first three components of the index.
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Fig. 3: Sedimentation graph for the correlation matrix of the MQOLI by AGEB.
Source: Own estimates based on the INEGI, Population and Housing Census, 2010.
2
The classification of the KMO measure is: 0.90 to 1.0, excellent; 0.80 to 0.89, meritorious; 0.70 to 0.79, medium; 0.60 to 0.69,
mediocre; 0.50 to 0.59, miserable; and less than 0.49, unacceptable.
3
Bartlett's Sphericity Test checks whether the correlation matrix is an identity matrix, that is, that it has no significant correlation
(p> 0.05) between variables, CONAPO (2010).
4
Criterion called the arithmetic mean: the components with the steepest slopes are retained, CONAPO (2010).