Abstract
Statistical analysis was applied to the study of Oukaimeden rock art as a way to obtain chronological information. By means of correspondence analysis we identified trends in the representation of the various individual motifs in the valley rock art. Subsequently we analyzed recurrent associations and overlappings, which led us to the last scale of analysis: the dating of rock art stations.
Highlights
No doubt, one of the most complex challenges the ARPA project has dealt with was the spatial and chronological understanding of rock art engravings, as a preliminary step to its interpretation within Oukaïmeden history
Statistical analysis was applied to the study of Oukaïmeden rock art as a way to obtain chronological information
By means of correspondence analysis we identified trends in the representation of the various individual motifs in the valley rock art
Summary
One of the most complex challenges the ARPA project has dealt with was the spatial and chronological understanding of rock art engravings, as a preliminary step to its interpretation within Oukaïmeden history. Some statistically good results have been of little use due to the scarcity of represented units, while others have been stylistically relevant but lacked chronological precision Even considering all these problems, correspondence analysis has proved to be a key element for the interpretation of the rock art of Oukaïmeden within its historical context, and can help to establish new ways to organize and understand High Atlas rock art. The results of the correspondence analysis were fairly good, as the diagram showed a parabolic curve which marked the existence of a seriation within the data, with three main groups and a prolongation of one of the legs of the parabola (fig.2) The analysis of these three groups proved, that they were associated to three main kinds of weapons -maces, halberds and daggers- and different variables related to the shapes of their hilts and blades. The statistical test has been up for the challenge, benefiting from a well sized sample, a good data analysis and an accurate set of variables
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