In this exploritory data analysis (EDA), we will use various statistical approaches to visualize the relationship between the composition of amygdala and acc levels in participants' brain and their political orientation: one and two dimensional histograms and kernel density estimator (KDE); scatter plots and line charts of the mean, variance, and skew, based on variable orientation and conditional distributions.
We will establish that the two variables (amygdala, acc) have a low interdependent, using probability and statistics theory, with visualization of their respective mutual information and permutation scores. As you will see in this analysis, we can extract so much more information from density estimation than simple summary statistics (e.g., the sample mean).
This analysis is based on the study by Kanai, R., Feilden, T., Firth, C. and Rees, G., 2011, “ Political orientations are correlated with brain structure in young adults”.
