So the problem is how you compare a city with 5/6 exits like Branford, CT USA with 143/208 like Mountain View. Is Branford that much better because 5/6 > 143/208 ? Mostly all you know is that the error in your estimate is much larger for Branford than for Mountain View, because your value of n is 6 vs 208. You can't say with statistical confidence that Branford is better.
So one trick to punish the little n locations is to do some smoothing. Laplace smoothing is to add 1 for all outcomes, so 1 success to x and one failure, meaning we add 2 to n. That also means that nothing gets exactly to 0.0 or 1.0. The odds in Saint Petersburg Russia aren't really 0.0 because the were 0/11. There is some chance you could succeed, so it gives you a better estimate of "unseen events".
The next thing you want to do is look at confidence intervals, rather than our point estimate of x/n or even (x+1)/(n+2). There are a number of formulas you can use, I used one built into R, a statistical modelling language. This gives you a lower and upper bound on your true estimate of the proportion. If the bounds is exact, then 95% of the time the interval will contain this true, unknown proportion.
The bounds on my smoothed counts are:
x+1 n+2 lb x1/n2 ub
Mountain View, CA USA 144 209 0.621 0.689 0.751
Branford, CT USA 6 7 0.421 0.857 0.996
Los Angeles, CA USA 56 180 0.244 0.311 0.384
To sort, it is often good to be conservative and use the lower bound. I used a 95%, which is good for saying Branford is better than LA, but might be a bit large for sorting. You could use a 90% or even 80% interval for that, if desired.
It is really crucial to take into account what you don't know when comparing fractions based on different values of n.
Hope this helps...
It does. Thank you.