Fix alignment by exp description (#348)

* fix explanation of alignment by exposure plot

* fix more typos

vignettes/cookbook_interpretation.Rmd

@@ -282,11 +282,11 @@ The variables in the table map to the figures as follows:
 
 ### Net Aggregate Alignment by Financial Exposure
 
-The net aggregate alignment by financial exposure plot summarizes the financial exposure (y-axis) of a (grouped or ungrouped) loan book (dot color) by financial exposure to PACTA sectors (x-axis). Every sector is shown in a separate pane with equal scales, which allows comparing the significance of exposures across sectors. In this plot, the net aggregate alignment metric is presented as a continuous variable along the y axis, which allows for more nuance compared with the sankey plot. Exposures to very misaligned companies will influence the loan book level alignment more negaatively here, because the loan book level net aggregate alignment metric is a weighted mean of the underlying continuous company level net aggregate alignments weighted by the financial exposure. However, this addittional detail makes the plot slightly slower to read than the sankey plot. Generally, this plot emphasizes the scale of the net aggregate alignment more than the exposure and is therefore a good complementary plot to the sankey plot. The output data set can be found in the `../analysis/aggregated/data_scatter_alignment_exposure<...>.csv` file, where <...> will be replaced with the names of each of the groups in the variable set in the `by_group` parameter.
+The net aggregate alignment by financial exposure plot summarizes the net aggregate alignment metric (y-axis) of a (grouped or ungrouped) loan book (dot color) by financial exposure to PACTA sectors (x-axis). Every sector is shown in a separate pane with equal scales, which allows comparing the significance of exposures across sectors. In this plot, the net aggregate alignment metric is presented as a continuous variable along the y axis, which allows for more nuance compared with the sankey plot. Exposures to very misaligned companies will influence the loan book level alignment more negatively here, because the loan book level net aggregate alignment metric is a weighted mean of the underlying continuous company level net aggregate alignments weighted by the financial exposure. However, this additional detail makes the plot slightly slower to read than the sankey plot. Generally, this plot emphasizes the scale of the net aggregate alignment more than the exposure and is therefore a good complementary plot to the sankey plot. The output data set can be found in the `../analysis/aggregated/data_scatter_alignment_exposure<...>.csv` file, where <...> will be replaced with the names of each of the groups in the variable set in the `by_group` parameter.
 
 #### Example Plots Alignment by Exposure
 
-In this example plot, we analyse the net aggregate alignment by different bank types across six of the PACTA sectors. It is immediately obvious, that the exposures of credit unions in the oil & gas sector (misaligned) and in the power sector (aligned), as well as the exposures of less significant institutions in the coal sector (misaligned) have very pronounced net aggregate alignment metrics. This can be a further avenue for research into which specific companies seem to drive these results. It is also evident, that this plot does not make it very easy to compare the financial exposures across sectors, which highlights again one of the strengths of the sankey plot. Within sector however, financial exposure between groups can easily be differentiated.
+In this example plot, we analyse the net aggregate alignment by different bank types across six of the PACTA sectors. We can see that the exposures of credit unions in the oil & gas sector (misaligned) and in the power sector (aligned), as well as the exposures of less significant institutions in the coal sector (misaligned) have very pronounced net aggregate alignment metrics. This can be a further avenue for research into which specific companies seem to drive these results. It is also evident, that this plot does not make it very easy to compare the financial exposures across sectors, which highlights again one of the strengths of the sankey plot. Within sector however, financial exposure between groups can easily be differentiated.
 
 ```{r alignment_by_exposure, echo=FALSE, fig.cap='Fig. 13: Alignment by exposure plot of loan books grouped by bank type. Data is based on simulated test loan books.', fig.align='center', out.width='80%'}
 knitr::include_graphics("../man/figures/plot_scatter_alignment_exposure_bank_type.png")