Changes

::::[http://static.inky.ws/image/412/image.jpg Et voila], a better fit. This is an exponential curve fitted to the same data. Note that it fits much better in the region with the most words, but is a bit out for the earlier period where there are fewer words in the list. This is because we can more easily find suitable words from more recent periods, so naturally the pattern is most exact there. No doubt if we could go through a large, representative corpus and extract words uniformly, it would fit nicely all the way along. [[User:Jcw|Jcw]] 16:25, 20 June 2011 (EDT)

::::[http://static.inky.ws/image/412/image.jpg Et voila], a better fit. This is an exponential curve fitted to the same data. Note that it fits much better in the region with the most words, but is a bit out for the earlier period where there are fewer words in the list. This is because we can more easily find suitable words from more recent periods, so naturally the pattern is most exact there. No doubt if we could go through a large, representative corpus and extract words uniformly, it would fit nicely all the way along. [[User:Jcw|Jcw]] 16:25, 20 June 2011 (EDT)

:::::'''@Aschlafly: ''' Could you recount the words? My count gave me 26-51-103-210-18 (Sum: 408) instead of 26-52-103-208-18 (Sum: 408). Perhaps a fourth column for the century (or even better, the decade) could be added? That would make it much easier to keep track of the numbers!

:::::'''@Aschlafly: ''' Could you recount the words? My count gave me 26-51-103-210-18 (Sum: 408) instead of 26-52-103-208-18 (Sum: 407). Perhaps a fourth column for the century (or even better, the decade) could be added? That would make it much easier to keep track of the numbers!

:::::'''@Jcw: ''' I don't think that your ''better fit'' is the function which Aschlafly has in mind: it should be <math>F_{theo}(t) = \frac{\#words }{15}</math><math>(2^{\frac{t-1599}{100}}-1)</math>, where ''#words'' is the number of words created before 2000, i.e., 390. This function touches/intersects the empirical cdf at the turn of each century, a fact which betrays the biased method of looking for these words.

:::::'''@Jcw: ''' I don't think that your ''better fit'' is the function which Aschlafly has in mind: it should be <math>F_{theo}(t) = \frac{\#words }{15}</math><math>(2^{\frac{t-1599}{100}}-1)</math>, where ''#words'' is the number of words created before 2000, i.e., 390. This function touches/intersects the empirical cdf at the turn of each century, a fact which betrays the biased method of looking for these words.