Dear community,
I'm doing a lm. In the independent variables I've got a categorical one.
Here is its histogram:
http://r.789695.n4.nabble.com/file/n3333638/altitude.png
I did this regression:
lmeo2.52f <- lm(dat82$IncAltuDom ~ dat82$hdom2+log(dat82$CV)+ dat82$CA+
dat82$FCC+ factor(dat82$IdAltitud))
I obtain:
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 8.78222 0.94619 9.282 3.72e-15 ***
dat82$hdom2 -0.30859 0.03875 -7.963 2.73e-12 ***
log(dat82$CV) -0.42943 0.24568 -1.748 0.0835 .
dat82$CA -2.98157 2.29904 -1.297 0.1977
dat82$FCC 0.02300 0.01067 2.156 0.0335 *
factor(dat82$IdAltitud)1 -0.12142 0.40361 -0.301 0.7642
factor(dat82$IdAltitud)2 0.24341 0.43451 0.560 0.5766
factor(dat82$IdAltitud)3 -0.64904 0.47114 -1.378 0.1714
factor(dat82$IdAltitud)4 -1.14334 0.67509 -1.694 0.0935 .
factor(dat82$IdAltitud)5 -2.13251 0.82463 -2.586 0.0112 *
I thought I need to recodify my factor,
q1 How can I do it?
q2 Apologies I'm pretty newbie with this, ... I don't know how to
interpret
the regression when factors ... The factors created by default, compare the
1st factor with the other 5? ... but what does it mean??? is it good in my
case ??
Thanks in advance, user at host.com
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