Gator, linear just means in the model parameters, not the actual functions.
Specifically :
f(x)=sum a_i * g_i(x)
is a linear model
so for example
1+a*x^10+c*Exp(-x)
is a linear model with paramters a and c, whereas
Sin(a*x)
isn't linear because it isn't of the form
<some parameter>*<somefunction>
Note the vast majority of nonlinear problems can be made linear with approximations.
As for statistics, these are trivial to collect. For example go into the for sale forum and take the last one hundred posts, find correlations between
-the price and the number of replies
-the price and the number of knives of that type sold
-the members # of posts and the price of the knives sold
Some of these are likely to turn up strong very simply correlations of the form a*x, some of them will show nothing outside of random correlation.
It is also trivial to gather such statistics in everyday life. The next time you are eating lunch say hello and smile at a random person who passes by then se if you can correlate :
-their age (estimate) to the number of returned smiles and hellos
-look at the influence of sex, do you get more returns from men or women (noting that an average is just a linear regression of a constant function).
-try different phrases, do the number of words/syllables correlate to the number of responces (hello,hi,nice day,good afternoon)
Use your imagination.
-Cliff