Stats in the Wild: Law School

This is good:
Law School and Stats

You went to law school to get away from stats. But it followed you. You know why? Cause you’re in the wild.

A note about the article: The author mentions in the first paragraph that “Usually, the investigator seeks to
ascertain the causal effect of one variable upon another—the effect of a price increase upon demand, for example, or the effect of changes in the money supply upon the inflation rate.”

One needs to be careful about the differences between correlation and causation. The investigator is often interested in establishing a causal relationship between two variables, but that can only be done through a well designed randomized experiment. If we do not have a randomly designed experiment, the best the investigator can do is establish a correlation between two varaibles. (More to come on the difference between causation and correlation.)

As wikipedia says:

“The concept of correlation is particularly noteworthy. Statistical analysis of a data set may reveal that two variables (that is, two properties of the population under consideration) tend to vary together, as if they are connected. For example, a study of annual income and age of death among people might find that poor people tend to have shorter lives than affluent people. The two variables are said to be correlated (which is a positive correlation in this case). However, one cannot immediately infer the existence of a causal relationship between the two variables. (See Correlation does not imply causation.) The correlated phenomena could be caused by a third, previously unconsidered phenomenon, called a lurking variable or confounding variable.”



Posted on October 21, 2008, in Uncategorized. Bookmark the permalink. Leave a comment.

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