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## R script for model with all inputs
## Data: https://modeanalytics.com/benn/reports/72c16eaaeefc
tracts <- read.csv("model_inputs.csv")
## By white population percent
full <- lm(trips ~ median_income + population + white_percent + distance_in_miles,data=tracts)
summary(full)
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.204e+04 2.149e+03 5.600 5.69e-08 ***
## median_income 6.346e-02 2.006e-02 3.163 0.00176 **
## population -7.785e-02 1.728e-01 -0.450 0.65282
## white_percent 4.748e+03 3.244e+03 1.464 0.14455
## distance_in_miles -2.840e+03 3.126e+02 -9.084 < 2e-16 ***
## ---
## Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
##
## Residual standard error: 7664 on 247 degrees of freedom
## Multiple R-squared: 0.5496, Adjusted R-squared: 0.5423
## F-statistic: 75.35 on 4 and 247 DF, p-value: < 2.2e-16
## By black population percent
black_only <- lm(trips ~ median_income + population + black_percent + distance_in_miles,data=tracts)
summary(black_only)
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.579e+04 2.199e+03 7.180 8.17e-12 ***
## median_income 6.815e-02 1.515e-02 4.498 1.05e-05 ***
## population -1.101e-01 1.716e-01 -0.641 0.5218
## black_percent -6.943e+03 2.858e+03 -2.429 0.0158 *
## distance_in_miles -2.868e+03 2.987e+02 -9.601 < 2e-16 ***
## ---
## Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
##
## Residual standard error: 7607 on 247 degrees of freedom
## Multiple R-squared: 0.5563, Adjusted R-squared: 0.5491
## F-statistic: 77.42 on 4 and 247 DF, p-value: < 2.2e-16
## With nightime trips as dependent varible
after_8 <- lm(after_8_trips ~ median_income + population + white_percent + distance_in_miles,data=tracts)
summary(after_8)
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.991e+03 8.641e+02 5.776 2.29e-08 ***
## median_income -2.320e-03 8.065e-03 -0.288 0.7739
## population -7.622e-02 6.949e-02 -1.097 0.2738
## white_percent 2.950e+03 1.304e+03 2.262 0.0246 *
## distance_in_miles -9.634e+02 1.257e+02 -7.666 4.06e-13 ***
## ---
## Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
##
## Residual standard error: 3081 on 247 degrees of freedom
## Multiple R-squared: 0.3827, Adjusted R-squared: 0.3727
## F-statistic: 38.28 on 4 and 247 DF, p-value: < 2.2e-16
## With nightime trips as dependent varible, by black population ony
after_8_black_only <- lm(after_8_trips ~ median_income + population + black_percent + distance_in_miles,data=tracts)
summary(after_8_black_only)
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 7.188e+03 8.790e+02 8.177 1.53e-14 ***
## median_income 1.510e-03 6.055e-03 0.249 0.803301
## population -9.184e-02 6.859e-02 -1.339 0.181815
## black_percent -3.937e+03 1.142e+03 -3.447 0.000667 ***
## distance_in_miles -9.869e+02 1.194e+02 -8.266 8.56e-15 ***
## ---
## Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
##
## Residual standard error: 3041 on 247 degrees of freedom
## Multiple R-squared: 0.3988, Adjusted R-squared: 0.3891
##