From what I've gathered, generally speaking people use weighted 3 year park factors.

My question is, why?

For one, we have a control: The park itself (Unless the team makes changes to dimensions/field/ect).

There are two variables I can think of that then come into play: Weather and actual baseball results.

Since the control is what we are measuring, wouldn't that mean that it'd be smarter to use the biggest sample size possible, since the other two variables can skew the results?  I mean, there's a reason home/away splits for a player aren't generally taken into factor, because there's huge random variance in it.  I mean yes, the park will effect the baseball results, but there's so much variance in baseball results and that's why we always use the biggest sample size possible.  And weather is going to be weather, again sample size ftw.

And yet people will say things like "Stadium Field Park played like a pitchers park this year, even though it was a hitters park last year."  The park itself didn't change though.  The results inside the park changed, sure, but the park stayed the same, the results changed because of other variables.  So what am I missing? Why use weighted 3 year park factors over the biggest sample size possible?

And just as a lesser question: What's the reason behind getting K% by K/AB instead of K/PA?  Fangraphs does K/AB but I don't really understand why they do that instead of K/PA (And other places, like statcorner, do K/PA).  Does it even matter?