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Observations of non-random distribution of galaxies with opposite spindirections have recently attracted considerable attention. Here, a method foridentifying cosine-dependence in a dataset of galaxies annotated by their spindirections is described in the light of different aspects that can impact thestatistical analysis of the data. These aspects include the presence ofduplicate objects in a dataset, errors in the galaxy annotation process, andnon-random distribution of the asymmetry that does not necessarily form adipole or quadrupole axes. The results show that duplicate objects in thedataset can artificially increase the likelihood of cosine dependence detectedin the data, but a very high number of duplicate objects is required to lead toa false detection of an axis. Inaccuracy in galaxy annotations has relativelyminor impact on the identification of cosine dependence when the error israndomly distributed between clockwise and counterclockwise galaxies. However,when the error is not random, even a small bias of 1% leads to a statisticallysignificant cosine dependence that peaks at the celestial pole. Experimentswith artificial datasets in which the distribution was not random showed strongcosine dependence even when the data did not form a full dipole axis alignment.The analysis when using the unmodified data shows asymmetry profile similar tothe profile shown in multiple previous studies using several differenttelescopes.

Analysis of the alignment of non-random patterns of spin directions in populations of spiral galaxies