why my R^2 is so small while there do seem to be a dependency there?

Hello,

Hoe did you get 0.002? Can you ?dput your data?

d <- read.table(text = "
factor  observation
-0.003       -2
-0.002       -2
-0.001       -1
0.000         1
0.001         0
0.002         1
0.003         2
", header = TRUE)

fit <- lm(observation ~ 0 + factor, data = d)
summary(fit)  # R2 is 0.8595, not 0.002

Hope this helps,

Rui Barradas

Em 04-08-2013 18:19, CHEN, Cheng escreveu:

Hi gurus!

What I need to do is to find a model, which can predict what the *
observation* should look like given a *factor* input.

i am doing a simple linear fit in R:

lm(observation~0+factor, data=d), the R^2 is 0.002, which is really small.

however, when I do a 'SELECT AVG observation by 0.001 BRACKET factor',
there result is something like:

*factor* | *average observersion*

-0.003       -2

-0.002       -2

-0.001       -1

0.000         1

0.001         0

0.002         1
0.003         2


from a user perspective, i definitely see a pattern here, but somehow this
pattern is not captured by a linear model. Is my understanding correct?

so R gurus, which model do you suggest me to try for such data?

Thanks!