We see [\ref{fig:bootstrap_distributions}] that for Maputo and Bulawayo the mean El Niño value is low enough that it appears that it is unlikely, although clearly not impossible, for it to be generated by selecting seventy-five random elements. The values for Maseru and Petoria, however, fall within the range of values easily obtained by sampling at random. Even though both have on average negative anomalies during identified El Niño periods, this analysis suggests that it is less likely that these associations are not coincidental, or perhaps rather that El Niño is not a singular dominant driver for variation in those regions.

So how does considering the significance of the statistics affect our composite images [\ref{fig:comp_examples}]? What is the result if we perform the same test [\ref{fig:bootstrap_distributions}] for each grid cell and block out those that don’t pass?