Summary statistics for vehicle dataset : by Jean Roth , jroth@nber.org , 22 Apr 2016 Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- state | 56,084 28.21133 15.63885 1 56 ve_forms | 56,084 1.697703 .8151218 1 16 harm_ev | 56,084 13.14612 6.792241 1 99 man_coll | 56,084 1.712841 1.917797 0 9 hit_run | 56,084 .0190607 .1817515 0 2 -------------+--------------------------------------------------------- veh_no | 56,084 1.348852 .615083 1 16 make | 56,084 28.89792 27.3567 1 99 model | 56,084 38.14772 39.86483 0 99 body_typ | 56,084 18.7355 23.28119 1 99 mod_year | 56,084 70.87217 5.614761 0 99 -------------+--------------------------------------------------------- reg_stat | 56,084 28.252 16.62446 0 99 rollover | 0 j_knife | 0 trav_sp | 56,084 77.06735 29.62609 0 99 tow_veh | 56,084 .0106982 .1028784 0 1 -------------+--------------------------------------------------------- spec_use | 56,084 .0247843 .4011189 0 9 emer_use | 0 impact1 | 56,084 10.15759 11.49425 0 99 impact2 | 56,084 10.76621 14.15423 0 99 deformed | 56,084 5.189359 1.79782 0 9 -------------+--------------------------------------------------------- impacts | 56,084 1.186238 .7011335 0 9 towaway | 56,084 2.349547 1.885756 1 9 fire_exp | 56,084 .0234291 .1512634 0 1 ocupants | 56,084 3.182209 11.66668 0 99 deaths | 56,084 0 0 0 0 -------------+--------------------------------------------------------- veh_cf1 | 56,084 6.147903 23.67714 0 99 veh_cf2 | 56,084 6.055577 23.68883 0 99 m_harm | 0 chas_tr | 22,237 99 0 99 99 wgtcd_tr | 28,854 7.356935 3.123754 0 9 -------------+--------------------------------------------------------- vin_lngt | 56,084 44.43292 42.04094 2 99 vin_1 | 0 vin_2 | 0 vin_3 | 0 vin_4 | 0 -------------+--------------------------------------------------------- vin_5 | 0 vin_6 | 0 vin_7 | 0 vin_8 | 0 vin_9 | 0 -------------+--------------------------------------------------------- vin_10 | 0 fldcd_tr | 0 mcycl_ty | 0 dr_pres | 56,084 1.022627 .384615 1 9 dr_drink | 56,084 .1350653 .6722347 0 9 -------------+--------------------------------------------------------- l_state | 56,084 28.88234 17.10476 1 99 l_status | 56,084 3.177662 1.213184 0 9 l_restri | 56,084 1.542775 3.306161 0 9 dr_train | 56,084 6.882908 3.733017 0 9 viol_chg | 56,084 .4498074 1.470303 0 9 -------------+--------------------------------------------------------- prev_acc | 56,084 6.317096 23.38057 0 99 prev_sus | 56,084 6.123636 23.41847 0 99 prev_dwi | 56,084 5.924774 23.28871 0 99 prev_spd | 56,084 6.570983 23.16926 0 99 prev_oth | 56,084 6.53912 23.18741 0 99 -------------+--------------------------------------------------------- last_mo | 56,084 9.528136 22.9094 0 99 last_yr | 56,084 47.12137 37.84185 0 99 first_mo | 56,084 9.55301 22.91306 0 99 first_yr | 56,084 45.92706 37.04644 0 99 dr_cf1 | 56,084 22.32651 22.88221 0 99 -------------+--------------------------------------------------------- dr_cf2 | 56,084 10.41482 21.13424 0 99 dr_cf3 | 56,084 3.350724 16.05939 0 99 st_case | 56,084 282849 156267.2 10001 560208 mak_mod | 56,084 2927.94 2752.151 100 9999 vin_wgt | 48,950 6352.197 3386.217 0 9999 -------------+--------------------------------------------------------- whlbs_sh | 48,950 5150.464 4424.836 0 9999 whlbs_lg | 48,950 4692.884 4854.901 0 9999 mcycl_ds | 22,754 9881.659 842.1788 720 9999 vina_mod | 0 ser_tr | 0 -------------+--------------------------------------------------------- vin | 0 by Jean Roth , jroth@nber.org , 22 Apr 2016