When you are covering the subject of correlation analysis (Chapter 4) and want to provide an example that may interest your students (especially the sports-oriented ones), here is a 2 paragraph quote from a recent WSJ article (Sept.17, 2010,p.W-8). The article suggests that more than any major league baseball season in recent memory, the size of a team’s payroll isn’t tied to winning.
“According to estimated figures updated throughout the season, the correlation between a team’s player payroll and its winning percentage is 0.14, a number that makes the relationship almost statistically irrelevant. That figure is 67% below last year’s mark and is easily the lowest since the strike.”
“This outcome represents a stark reversal from the state of affairs a decade ago. In 1998, the correlation between payrolls and wins was 0.71, a figure that suggests a strong and significant tie. And in the 1999 season, when the correlation was 0.5, all eight teams that reached baseball’s playoffs were among the top ten spenders.”
This can make for a nice class discussion. First, it shows that terms from the text show up even on the sports page. But let the students compute the R squares for these correlations and interpret the relationships for those values. If the R-square was 0.504 in 1998, and 0.25 in 1999,what explains the rest of the variation?
I love the Journal’s sports section and hope you also find some of the statistics on that page interesting.