Summary statistics for vehicle dataset : by Jean Roth , jroth@nber.org , 22 Apr 2016 Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- state | 583 43 0 43 43 ve_forms | 583 1.569468 .7166845 1 5 harm_ev | 583 12.22985 6.252312 1 31 man_coll | 583 1.229846 1.637826 0 6 hit_run | 583 .0274443 .2176132 0 3 -------------+--------------------------------------------------------- veh_no | 583 1.284734 .541625 1 5 make | 583 24.24185 18.78413 1 99 model | 583 67.50943 41.98993 0 99 body_typ | 583 15.02573 21.9636 2 99 mod_year | 583 71.84906 5.643887 12 99 -------------+--------------------------------------------------------- reg_stat | 583 43.36192 4.35863 43 97 rollover | 583 .1955403 .5431681 0 2 j_knife | 0 trav_sp | 583 98.29846 7.797707 0 99 tow_veh | 583 .0034305 .0585204 0 1 -------------+--------------------------------------------------------- spec_use | 583 .0926244 .5728663 0 5 emer_use | 583 .0120069 .1090095 0 1 impact1 | 583 8.468268 6.083209 0 99 impact2 | 583 9.087479 5.964462 0 99 deformed | 583 4.35506 2.105264 0 9 -------------+--------------------------------------------------------- impacts | 583 .9794168 .527187 0 9 towaway | 583 2.439108 2.350546 1 9 fire_exp | 583 .0188679 .1361754 0 1 ocupants | 583 5.38765 18.5404 0 99 deaths | 583 .5317324 .7678718 0 11 -------------+--------------------------------------------------------- veh_cf1 | 583 .7255575 7.208492 0 99 veh_cf2 | 583 .5214408 7.092114 0 99 m_harm | 0 chas_tr | 497 99 0 99 99 wgtcd_tr | 516 8.753876 1.333469 0 9 -------------+--------------------------------------------------------- vin_lngt | 583 84.98628 31.99393 9 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 | 583 1.025729 .3483246 1 9 dr_drink | 583 .1903945 .3929495 0 1 -------------+--------------------------------------------------------- l_state | 583 43.67238 6.771482 1 99 l_status | 583 2.90566 1.269393 1 9 l_restri | 583 .1955403 1.147018 0 9 dr_train | 583 8.879931 .9944824 0 9 viol_chg | 583 .9879931 1.156868 0 9 -------------+--------------------------------------------------------- prev_acc | 583 16.98285 37.35117 0 99 prev_sus | 583 17 37.34363 0 99 prev_dwi | 583 16.99828 37.34443 0 99 prev_spd | 583 17.01715 37.33603 0 99 prev_oth | 583 17.27444 37.2257 0 99 -------------+--------------------------------------------------------- last_mo | 583 18.30875 36.86864 0 99 last_yr | 583 32.81304 42.72602 0 99 first_mo | 583 18.3259 36.86457 0 99 first_yr | 583 32.70497 42.61466 0 99 dr_cf1 | 583 26.35163 18.31393 0 99 -------------+--------------------------------------------------------- dr_cf2 | 583 12.68954 19.58122 0 99 dr_cf3 | 583 4.86964 14.20965 0 99 st_case | 583 431629.9 1505.347 430001 433251 mak_mod | 583 2491.695 1886.892 101 9999 vin_wgt | 561 9200.127 2241.424 1610 9999 -------------+--------------------------------------------------------- whlbs_sh | 561 8979.169 2844.679 866 9999 whlbs_lg | 561 8888.062 3102.742 0 9999 mcycl_ds | 500 9941.358 742.8518 123 9999 vina_mod | 0 ser_tr | 0 -------------+--------------------------------------------------------- vin | 0 by Jean Roth , jroth@nber.org , 22 Apr 2016