- update plots: sample_size, error_function_of_csa
- update legends: boxplot_atrophy, boxplot_csa

- expected trend and mean values on CSA boxplot
- mean values on atrophy boxplot
- add function for adding pearson's r and p-value stats
- add diff and std diff column in dataframe for sample size computation
- add longitudinal study sample size

change:
- correct difference between means (atrophy_% * CSA) on sample size plot
- correct x_label on error_function_of_CSA
- correct x_label on error_function_of_intra_cov
- automatize the detection of outliers on error_function_of_intra_cov_outlier

# Conflicts:
#	csa_rescale_stat.py

…ore this diff was computed from mean CSA across transformations)

- add comments

- normalize by the square of rescale for df['Normalized CSA in mm²']
- use poly1d when plotting trends in plots

- append fake values for pearson and and p_value for rescale =1

- un-comment concatenating csv files

- change iteration number for computing sample size and print message