1) The introduction discusses a number of different ways in which individuals have been able to measure, quantify and make predictions about seemingly immeasurable phenomena. Wine quality for instance is broken down to a simple formula that uses only a few pieces of readily accessible weather data. Baseball prospects are judged by statistical production rather than appearance (By the way I highly recommend the book Money ball that was referenced in this chapter and have a copy that will gladly loan out!). Can you think of something related to your school life/performance that might predictable? What types of variables would you look at to make a prediction?
2) Chapter one discusses massive amounts of data that various institutions possess. Google, the IRS, casinos, credit bureaus, know Alto more about us than we probably realize. The chapter mentions how Google can predict what news articles you would like to read based on knowing the 16 articles you previously have read. Since many of you have a Myspace or Face book page, think about the information that these websites may know about you? Now consider how these sites might use this information?
3) The chapter also discusses how your credit score may now be used against you. You may not be able to get a job, insurance, or rent an apartment, if your credit score is questionable. Do some quick research about the types of things that affect your credit score. As a young person about to enter the “REAL” world (i.e. jobs, taxes, rent, loans,etc.) in a short period of time, this is pretty important. Can you think of anyone close to you who has mismanaged their credit? What if any consequences did they suffer?
4) Regression is the technique that is discussed in depth in this chapter. The author makes it pretty clear what the two biggest benefits to the regression technique are. What are these benefits, and can you give an everyday example of each?
5) Lastly, the chapter mentions the idea of “regression to the mean”. One example it gives is that children of tall parents most likely will be tall, but not as tall as their parents were. You could easily substitute the word “short” in for tall and the statement would still be true. Can you think of a situation in your academic life where regression to the mean comes into play?
