text: You want something where there is a linear relationship and data are easy to get.\n\nAn easy choice would be to use stock data.  Regrss the returns of a particular stock against the returns of the S&P 500.   You can find the data on Yahoo! Finance (take raw prices -- divide each price by the previous price and subtract one to get the returns).  While this wiould be easy to get, it would not be unique -- lots of people do this.\n\nSomething that might be fun might involve regressing some characteristic of a city against the population.  \n\nHere is my idea:  Find 15 big cities, 15 medium sized cities and 15 small towns.  Get the population of each city.  Then find some statistic for each city.  Perhaps it is the number of homes with internet connectins, perhaps it is the number of felonies, perhaps it is the number of people with AIDs or some other disease, perhaps it is the number of universities nearbye.  Then do a regression of that statistic to see if the size of the city is a significant predictor of that statistic.\n\nYou need to be careful -- I suspect some of these are related to size but not in a linear way.  For example AIDs cases are probably related to size but not linear -- since many AIDs cases in small towns probably moved.  Similarly, rape or burglary are probably more likely to be linearly related than murder.  For those that aren't linear, you might try regressing LN(statistic).\n\nGood luck