I just completed an interesting project with a researcher in Philadelphia. We were looking at political cultures and used correlation statistics to find certain links within the data. To be specific we used Ordinal data and Spearman's Rho.
There are generally four types of data: Nominal, which are usually categorical. These include male or female: red car or green car: things that can be neatly categorized.
Next we have ordinal data. Here, objects are ranked. First in class, second in line and so on. This is the type of data we chose to use. We took political cultures and ranked them under a pre-defined system.
The third type of data is interval data. This allows the ordering of data and have a definite space between each data point. One example is the Farenheit measurement for temperatures. Although moving for twenty to thirty Farenheit is the same amount of change as moving from fifty to sixty Farenheit, there is no definite zero point.
The last type of data, ratio...
I had an excellent session with a student who is working on a Law and Ethics course. It was a good way to review the boundaries between law, ethics and economics. The law is famously open-ended. Every rule has an exception and every argument has a counter-argument. But of course just because you can think of an exception or an argument does not mean you need to bring it up. Take this example, from our session: The Food and Drug Administration exempts a company from a certain regulation. Later it comes out that a member of the FDA's governing board took a bribe from the company. It is not clear whether the FDA knew about the bribe that resulted in that member casting the tie-breaking anti-regulation vote.
Clearly, the FDA has all sorts of defenses at its disposal, especially if they did not know about the bribe. Clearly they can argue a number of defenses, including procedural ones which don't touch on whether they were aware of the issues at hand. But do they want to make this...