# Help me interpret this negative linear regression [closed]

This is the output I have for a multiple linear regression I did in R.

Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept)                            1.936e+01  8.196e-01  23.627  < 2e-16 ***
dados3$$income -1.278e-03 5.784e-04 -2.209 0.02721 * dados3$$indice_gini                    -1.430e+01  1.247e+00 -11.470  < 2e-16 ***
dados3$$month_wage -1.775e-01 9.515e-02 -1.866 0.06212 . dados3$$perc_extreme_poor_kids          3.854e-02  1.216e-02   3.169  0.00154 **
dados3$$perc_poor_kids 2.159e-01 1.148e-02 18.812 < 2e-16 *** dados3$$perc_pop_with_prop_Wc           5.055e-02  6.021e-03   8.397  < 2e-16 ***
dados3$$perc_pop_w_houses 4.297e-02 7.924e-03 5.423 6.12e-08 *** dados3$$perc_pop_with_trash_disposal   -7.045e-03  6.520e-03  -1.080  0.27999
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 4.038 on 5555 degrees of freedom
Multiple R-squared:  0.6804,    Adjusted R-squared:  0.6799
F-statistic:  1478 on 8 and 5555 DF,  p-value: < 2.2e-16


In my interpretation, the equation yielded a negative regression. Where as one independent variable decreases, it increases the dependent variable (in this case child mortality rates). An interesting observation I noticed was that the gini coef decreases, and meanwhile the child mortality increases (the contrary was supposed to happen). Is my interpretation correct?

• Your interpretation is correct, but you almost certainly have collinearity which can do weird things to parameter estimates. Have you checked for collinearity? – Peter Flom - Reinstate Monica Nov 8 '19 at 14:37