How to interpret a Spearman plot Given the following data:
library("fifer")
homicidiostaxa0515 = c(26.1 26.6 26.7 27.2 27.8 27.4 29.4 28.6 29.8) #BR's homicide rate 2005-14
popcartaxa0515 = c(196.2 214.8 229.6 247.3 260.2 267.5 283.5 289.3 299.7) #BR's inmate rate 2005-14

I ran Spearman's correlation test on them and the result is as following:
data:  popcartaxa0515 and homicidiostaxa0515
S = 4, p-value = 0.0001653
alternative hypothesis: true rho is not equal to 0
sample estimates:
  rho 
0.9666667 

Found a spearman.plot function in the package above,
ran it as below:
spearman.plot(popcartaxa0515, homicidiostaxa0515, dcol = "blue", xlab="Taxa População Carcerária/100khab", ylab="Taxa de Homicídios/100khab")

and it returned something like this:
I'm an undergraduate in a Brazilian law college, and I really have no clue on how to read this graphic. Mounting questions pop up in my head, but I'll have to ask them later.
 A: The large square portion is a scatterplot of the variable ranks: the smallest x value is plotted at x=1, the second smallest at x=2, and so on; likewise, the smallest y value is plotted at y=1, the second smallest at y=2, etc. (The axis labels help make that clear.) 
The Spearman correlation is the Pearson correlation coefficient of this scatterplot.  The fitted line goes through the middle of the ranks. Since the two sets of ranks must have the same variance (at least when there are no ties within the x's or the y's), the slope of the fitted line is exactly the Spearman correlation.
The other plots are rug-like plots on different axes.  (Possibly they would turn into histogram-like plots with more data.) They establish the correspondence between rank and value for each variable.  Because they appear to be drawn accurately on linear scales, they graphically depict the marginal distributions.  The fitted (blue) curves are likely Normal densities based on the means and variances of the data.  With small amounts of data they need to be ignored; with larger amounts of data they might be useful as a reference to gauge the degree of asymmetry, lengths of tails, etc.
