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Subjective classification of spiral galaxies is not sufficient for studyingthe effect of bars on their physical characteristics. In reality the problem isto comprehend the complex correlations in a multivariate parametric space.Multivariate tools are the best ones for understanding this complexcorrelation. In this work an objective classification of a large set (26,089)of spiral galaxies was compiled as a value added galaxy catalogue from sdss DR15 virtual data archive.  Initially for dimensionality reduction, Independent Component Analysis isperformed to determine a set of Independent Components that are linearcombinations of 48 observed features (namely ionised lines, Lick indices,photometric and morphological properties). Subsequently a K-means clusteranalysis is carried out on the basis of the 14 best chosen IndependentComponents to obtain 12 distinct homogeneous groups of spiral galaxies. Amongstthese, 3 groups are the oldest ones (1.6 Gyr - 5.9 Gyr), while 5 groups fall inthe medium aged category (1.4 Gyr - 1.6 Gyr), 2 groups consist of only unbarredspirals, 1 group is the youngest one and the remaining one is an outlier. Inmany groups there are clear indication of recurrent bar formation phenomenawhich is consistent with few previous simulation works. In order to study therobustness a second method of clustering by Gaussian Mixture Modeling Method(GMMBC) is applied.

Investigation of the Effect of Bars on the Properties of Spiral Galaxies: A Multivariate Statistical Study