Dear R-users,
Why variables that appear correlated with dependent variable in a scatterplot,
results not correlated in the summary of linear model, and vice versa?
I mean, variable "Longitude" (see the example below) is correlated (***) with
dependent variable in the linear model. But if I made a scatterplot the r2 is
very low.
How can I interpretate the information of command summary()?
Thank you in advance,
Francesco
#command for summary() of linear model
>summary(model_example)
Call:
lm(formula = dmp ~
Latitude + Longitude + Year + Tot.Prod + RFE.Cum.JASO.,
data = senegal5)
Residuals:
Min
1Q Median 3Q
Max
-676.49 -195.77 -33.06
113.34 816.17
Coefficients:
Estimate Std. Error
t value Pr(>|t|)
(Intercept) -3.283e+05 4.505e+04
-7.288 4.41e-11 ***
Latitude -6.100e+01 1.990e+02
-0.307 0.7598
Longitude -3.617e+02 8.639e+01
-4.187 5.60e-05 ***
Year 1.604e+02 2.300e+01
6.973 2.15e-10 ***
Tot.Prod -4.893e+00 1.565e+02
-0.031 0.9751 RFE.Cum.JASO. 2.525e+00 4.529e-01
5.575 1.68e-07 ***
---
Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1
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