What I Study: Regression Analysis & Modeling
There are five required first-year courses, three of these deemed "theory" and the other two "applied."
Regression Analysis and Modeling is an applied course. The basic idea here is
relating quantitative variables to one another. A simple example is as follows: say we want to attempt to predict peoples' weight ("response variable") based on their height ("explanatory variable"). On average, you would expect that heavier people would be taller.
So in regression analysis, you are essentially interested in two things: 1) prediction (i.e. can we predict the average weight of a person who is, say, 6'2" tall) and 2) quantifying the effect of the explanatory variable on the response (i.e. on average, how much does a person's weight increase as his height increases?).
Does this make sense?
posted by Byran @ 12:05 PM
6 comments
6 Comments:
No.
Ok, tell me what's unclear.
Let me try to understand again.
Tell me if this means I understand: According to my weight, I should be about 6'8".
I understand that, though I never had it explained in that manner before.
ITF, two words: "on average." The predictions that a regression would make are "average" predictions, meaning there would be some six-footers who weigh less than the regression would predict and some who would weigh more.
Makes sense to me.
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