For example, earthquakes are measured logarithmically. An earthquake with a rating of 5 is 10 times more severe than one with a rating of 4, and 10^2 = 100 times more severe than one with a rating of 3.
log scale, as the name indicates, is just a scaling factor. It makes the very big data easely represented. ex: pH=-log([H+]). If you want to represent [H+] you need to use huge numbers. On the other hand, pH could be conveniently represented by numbers ranging between (usualy) 0 and 14.
December 3rd, 2008 at 1:39 pm
Data is increasing lots faster than linearly.
For example, earthquakes are measured logarithmically. An earthquake with a rating of 5 is 10 times more severe than one with a rating of 4, and 10^2 = 100 times more severe than one with a rating of 3.
December 6th, 2008 at 2:25 am
log scale, as the name indicates, is just a scaling factor. It makes the very big data easely represented. ex: pH=-log([H+]). If you want to represent [H+] you need to use huge numbers. On the other hand, pH could be conveniently represented by numbers ranging between (usualy) 0 and 14.