Summary statistics for vehicle dataset : by Jean Roth , jroth@nber.org , 18 Apr 2016 Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- vin | 0 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 vin_11 | 0 vin_12 | 0 state | 50,660 27.40276 16.22722 1 56 veh_no | 50,660 1.457442 1.331769 1 51 -------------+--------------------------------------------------------- ocupants | 50,660 1.725819 4.300631 0 99 make | 50,660 34.18636 25.86598 1 99 model | 50,660 354.9135 303.755 1 999 body_typ | 50,660 26.60898 27.98523 1 99 reg_stat | 50,660 30.6897 21.91389 0 99 -------------+--------------------------------------------------------- owner | 50,660 1.650355 1.306725 0 9 rollover | 50,660 .3167193 .6857311 0 2 j_knife | 50,660 .0741413 .3036044 0 3 trav_sp | 50,660 77.64053 29.09903 0 99 haz_inv | 50,660 1.002803 .0528696 1 2 -------------+--------------------------------------------------------- haz_plac | 50,660 .006968 .1587409 0 8 haz_cno | 50,660 .0497631 1.893259 0 88 haz_rel | 50,660 .0068101 .1839753 0 8 tow_veh | 50,660 .0891038 .4909771 0 9 v_config | 50,660 .7341492 4.995131 0 99 -------------+--------------------------------------------------------- cargo_bt | 50,660 1.616206 11.39994 0 99 spec_use | 50,660 .029392 .4306511 0 9 emer_use | 50,660 .0017765 .0421121 0 1 impact1 | 50,660 11.29392 13.79331 0 99 impact2 | 50,660 11.74228 14.98488 0 99 -------------+--------------------------------------------------------- underide | 50,660 .0334583 .4484585 0 9 deformed | 50,660 5.354481 1.510932 0 9 impacts | 50,660 1.313778 .7085107 0 9 towaway | 50,660 1.97803 .8367927 1 9 fire_exp | 50,660 .0310896 .1789376 0 2 -------------+--------------------------------------------------------- veh_cf1 | 50,660 2.312831 11.79478 0 99 veh_cf2 | 50,660 1.092716 10.2801 0 99 veh_man | 50,660 5.519779 11.02614 1 99 avoid | 50,660 3.47049 3.603711 0 8 m_harm | 50,660 14.2074 11.94419 1 99 -------------+--------------------------------------------------------- deaths | 50,660 .6336952 .604625 0 17 seq1 | 50,660 31.28251 25.47655 1 99 seq2 | 50,660 20.76812 25.48325 0 99 seq3 | 50,660 11.05134 20.26027 0 99 seq4 | 50,660 5.100651 14.33079 0 99 -------------+--------------------------------------------------------- seq5 | 50,660 2.143762 9.558203 0 99 seq6 | 50,660 .7877418 5.75224 0 99 vin_lngt | 50,660 16.93393 .6695438 5 17 bus_use | 50,660 .0284051 .4216857 0 9 gvwr | 50,660 .2708251 .9206703 0 9 -------------+--------------------------------------------------------- unittype | 50,660 1 0 1 1 mcarr_i1 | 50,660 5.296486 18.27516 0 99 st_case | 50,660 274734.4 162191 10001 560139 haz_id | 50,660 9.959811 255.708 0 8888 mak_mod | 50,660 34541.27 26025.56 1001 99999 -------------+--------------------------------------------------------- mod_year | 50,660 2141.24 1053.804 1928 9999 vina_mod | 0 ser_tr | 0 vin_bt | 0 mcarr_i2 | 0 -------------+--------------------------------------------------------- fldcd_tr | 0 mcarr_id | 0 whlbs_sh | 45,515 1543.193 2029.375 0 9999 whlbs_lg | 45,515 778.7666 2267.464 0 9999 mcycl_ds | 7,522 3914.566 4208.537 49 9999 -------------+--------------------------------------------------------- vin_wgt | 29,491 3809.941 2038.111 0 9999 wgtcd_tr | 18,456 3.852948 3.18433 1 9 dr_pres | 50,660 1.020726 .2072644 1 9 dr_drink | 50,660 .2277142 .4193613 0 1 l_state | 50,464 29.00725 19.11745 1 99 -------------+--------------------------------------------------------- l_type | 50,464 1.211537 1.354704 0 9 l_status | 50,464 5.486525 1.753947 0 9 cdl_stat | 50,464 1.012583 2.392591 0 9 l_endors | 50,464 .187936 1.157868 0 9 l_compl | 50,464 2.933378 1.198772 0 9 -------------+--------------------------------------------------------- l_restri | 50,464 1.006975 1.833321 0 9 violchg1 | 50,464 4.183557 16.91501 0 99 violchg2 | 50,464 2.825539 14.88338 0 99 violchg3 | 50,464 2.191463 13.78666 0 99 prev_acc | 50,464 9.649215 29.00995 0 99 -------------+--------------------------------------------------------- prev_sus | 50,464 3.960348 18.6031 0 99 prev_dwi | 50,464 3.670458 18.61884 0 99 prev_spd | 50,464 3.910055 18.58284 0 99 prev_oth | 50,464 3.906963 18.58669 0 99 last_mo | 50,464 6.288344 18.5166 0 99 -------------+--------------------------------------------------------- first_mo | 50,464 6.271738 18.52102 0 99 dr_cf1 | 50,660 22.01518 26.34954 0 99 dr_cf2 | 50,660 15.2321 24.8724 0 99 dr_cf3 | 50,660 7.907264 21.65923 0 99 dr_cf4 | 50,660 3.428247 16.25509 0 99 -------------+--------------------------------------------------------- dr_wgt | 50,464 406.2522 368.4019 55 999 dr_hgt | 50,464 121.6626 215.8745 36 999 last_yr | 50,464 1184.101 1977.851 0 9999 first_yr | 50,464 1183.852 1977.747 0 9999 dr_zip | 50,464 52792.51 27730.61 0 99999 -------------+--------------------------------------------------------- month | 50,660 6.61593 3.397526 1 12 harm_ev | 50,660 16.4075 11.84804 1 99 man_coll | 50,660 2.246625 5.383683 0 99 hit_run | 50,660 .0803395 .4057712 0 5 ve_forms | 50,660 1.908883 2.154202 1 51 by Jean Roth , jroth@nber.org , 18 Apr 2016