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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 ‘ ’
1 

 

 		 	   		  
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