R is a programming language for statistical computing and graphics. To install R, required installation files can be found in the following link:

Download RStudio

Clear memory

rm(list = ls())

Load data

tripdata = read.csv("D:/Projects/20-102/Project Task/Task 4/R code/HH trip data_base model.csv",header=TRUE)
summary(tripdata)
##   HTRIPS_base         worker         retired           hmaker      
##  Min.   : 0.000   Min.   :0.000   Min.   :0.0000   Min.   :0.0000  
##  1st Qu.: 4.000   1st Qu.:1.000   1st Qu.:0.0000   1st Qu.:0.0000  
##  Median : 7.000   Median :1.000   Median :0.0000   Median :0.0000  
##  Mean   : 9.115   Mean   :1.298   Mean   :0.2816   Mean   :0.1138  
##  3rd Qu.:13.000   3rd Qu.:2.000   3rd Qu.:0.0000   3rd Qu.:0.0000  
##  Max.   :64.000   Max.   :5.000   Max.   :4.0000   Max.   :2.0000  
##     student          children          zero_veh         car_ls_drv    
##  Min.   :0.0000   Min.   : 0.0000   Min.   :0.00000   Min.   :0.0000  
##  1st Qu.:0.0000   1st Qu.: 0.0000   1st Qu.:0.00000   1st Qu.:0.0000  
##  Median :0.0000   Median : 0.0000   Median :0.00000   Median :0.0000  
##  Mean   :0.6813   Mean   : 0.6072   Mean   :0.04145   Mean   :0.1047  
##  3rd Qu.:1.0000   3rd Qu.: 1.0000   3rd Qu.:0.00000   3rd Qu.:0.0000  
##  Max.   :8.0000   Max.   :10.0000   Max.   :1.00000   Max.   :1.0000  
##   car_grt_wrk      inc_grt_100    
##  Min.   :0.0000   Min.   :0.0000  
##  1st Qu.:0.0000   1st Qu.:0.0000  
##  Median :1.0000   Median :0.0000  
##  Mean   :0.5382   Mean   :0.1941  
##  3rd Qu.:1.0000   3rd Qu.:0.0000  
##  Max.   :1.0000   Max.   :1.0000

Model estimation

hhtrip_base_model = lm(HTRIPS_base~worker+retired+hmaker+student+children+zero_veh+car_ls_drv+car_grt_wrk+inc_grt_100, data = tripdata)

Model outputs

summary(hhtrip_base_model)
## 
## Call:
## lm(formula = HTRIPS_base ~ worker + retired + hmaker + student + 
##     children + zero_veh + car_ls_drv + car_grt_wrk + inc_grt_100, 
##     data = tripdata)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -24.211  -3.431  -0.814   2.710  58.016 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  2.13800    0.16667  12.828  < 2e-16 ***
## worker       2.40296    0.08417  28.549  < 2e-16 ***
## retired      1.00790    0.11938   8.443  < 2e-16 ***
## hmaker       1.71221    0.19010   9.007  < 2e-16 ***
## student      2.05799    0.10586  19.440  < 2e-16 ***
## children     2.18942    0.10763  20.342  < 2e-16 ***
## zero_veh     0.66473    0.30717   2.164   0.0305 *  
## car_ls_drv   0.77831    0.19078   4.080 4.55e-05 ***
## car_grt_wrk  0.89015    0.13326   6.680 2.52e-11 ***
## inc_grt_100  0.30067    0.14060   2.139   0.0325 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 5.568 on 10268 degrees of freedom
## Multiple R-squared:  0.4404, Adjusted R-squared:  0.4399 
## F-statistic: 897.8 on 9 and 10268 DF,  p-value: < 2.2e-16

Here, worker = Number of workers, retired = Number of retired persons, hmaker = Number of homemakers, student = Number of students, children = Number of children, zero_veh = Zero vehicle household, car_ls_drive = Household with cars < drivers, car_grt_wrk = Household with cars > workers, inc_grt_100 = Household income > $100,000