I'm posting this in this forum because I think the question is related to stats. If it's not, I'm fine with it being moved over to Stackoverflow.
I have data in R and am trying to fit a linear model to it. Here's what the data looks like (sorry that it's not reproducible, it's just too much data to type out). The colored dots are based on density of points. The black line is what a linear model is returning as the best fit line (via lm(y~x)
which spits out a slope of 0.67
and an intercept of 0.002
) and the dashed line is what I would think the best fit line should be (slope of 5
, intercept of -3
).
Why is R's lm
method giving me a line which looks like it doesn't fit at all. Is it true that that line is better fitting than the dashed line I propose?
dput(data)
, which would probably be large but doable. $\endgroup$