The standard deviation can be directly obtained by rooting the variance we previously introduced. The meaning of this measure is exactly the same as the previous one, except that it is expressed employing the same unit of measure of the originating variable. This allows you to easily understand how relevant the amount of variation your variable expresses is. We formally derive the standard deviation as follows:

Employing R, we compute the standard deviation with the sd() function:

cash_flow_report %>% 
 select(cash_flow) %>% 
 unlist() %>% 
 sd()

This results in a more human 10,987.38 euros. Just to put this in the right context, we should recall that the minimum cash flow was 45,089.21, and the maximum was 132,019.06, so we are dealing with a small amount here.

If you think about it, this is coherent with what we found looking at the interquartile range that lets us conclude about the population behind quite homogeneous within the first and third quartile. Reading the story behind the numbers, we can hint that our profits have to have remained quite stable from 2014 onward, and this makes this recent drop even more suspicious.