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I've got some baseball stats, RBIs by season, let's say:

player      s1  s2  s3
Brian_Giles 66  68  70
Joe_Thomas  71  72  71
Robin_Yount 71  69  68
Jim_Jones   66  66  65

And I want to do a simple linear regression using lm() on this data to predict their RBI #s in a 4th season. Would I need another variable here to create my formula? How would I most simply complete this linear regression?

I'm trying to work off of this tutorial (http://www.r-bloggers.com/wp-content/uploads/2009/11/simpleLinRegExample1.txt), which seems like I might need a second variable, (I'm new to linear regressions, obviously) but I can't figure out what it should be. The slope of a best-fit line for those three seasons of data?

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  • $\begingroup$ Is there a reason not to use each player's average as your prediction for the next season? $\endgroup$ – dsaxton Jul 27 '15 at 14:52
  • $\begingroup$ I mean, yeah, that makes the most sense, but I'm actually just trying to wrap my head around basic linear regressions and how they're implemented in R. If it means anything, another reason I want to use lm() is because I envision this type of linear model being ideal for golf scores, heading into the 4th round, for example -- the idea being if they're playing well, they'll only play better in that 4th round. Obviously flawed, but interesting, perhaps. $\endgroup$ – skathan Jul 27 '15 at 15:04
  • $\begingroup$ You will want to read about "regression to the mean" before you do that golf analysis! $\endgroup$ – whuber Jul 27 '15 at 15:53
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You can't run an lm this way. You would need a variable for time and then you could regress on that, but that model would violate the assumption of independent errors, so you probably would want to use a multi-level model (in R see nlme or mle4). Those models get tricky.

A linear model needs a dependent variable (in your case, RBI) and at least one independent variable. In your case, you could, for example, use the RBI from a single season and model it as a function of (e.g.) position or league or team or age or whatever. But you need an independent variable.

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