Open MPaw18 opened 2 months ago
Yes, but this is the same as:
> summary(lm_obj_pre)
Call:
lm(formula = form_pre, data = wpom3)
Residuals:
Min 1Q Median 3Q Max
-0.0025977 -0.0014165 -0.0001195 0.0007647 0.0048454
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.366e-02 8.178e-03 -1.670 0.1156
log(density) 1.391e-03 7.328e-04 1.898 0.0771 .
avgsal 3.619e-06 1.501e-06 2.411 0.0292 *
unemp 1.041e-04 2.336e-04 0.446 0.6622
ssusers -2.252e-04 6.002e-04 -0.375 0.7128
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.00222 on 15 degrees of freedom
Multiple R-squared: 0.785, Adjusted R-squared: 0.7276
F-statistic: 13.69 on 4 and 15 DF, p-value: 6.786e-05
Do you have an economic model expecting the crime rate to vary with the other explanatory variables? Maybe ssusers and unemp are irrelevant? Maybe creating the rate by population is misleading, as criminals do not necessarily commit crimes where they live?
https://github.com/wikpur/Spacial-Econometrics-Project/blob/f12e530994bb4025f811a1ba6b30d68c48c33c41/Spacial-Econometrics-Project.Rmd#L358
@rsbivand