As a follow-up to my [previous question](https://stats.stackexchange.com/questions/43842/transform-data-to-a-higher-dimensional-space), I want to use Fisher's classification method (I mean, projection method) to project the data given the fact that the two classes are normally distributed. How to approximate the distributions? How to project the data when it's already in a one dimensional space? I remember Fisher's idea (two classes) was to project the data from D-dimensional input space to one dimensional. I don't know why I can't work with real data examples when I know how the actual method works. Please someone guide me through this. 

The classes are:

$C\_1=\{3, 3.5, 4, 4.5, 5, 5.5, 7\} \cup \{15, 16, 17\}$

$C\_2=\{0,0.5,1,2\}\cup\{8,9,10,11,12,13\}\cup\{20,25,30\}$

And the data will be on the interval $[0,40]$ like in the previous question.