Summary statistics for person dataset : by Jean Roth , jroth@nber.org , 18 Apr 2016 Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- state | 102,197 27.45204 16.06412 1 56 county | 102,197 89.56024 94.34812 0 999 month | 102,197 6.737566 3.367385 1 12 day | 102,197 15.73734 8.91376 1 99 hour | 102,197 13.52309 8.847189 0 99 -------------+--------------------------------------------------------- minute | 102,197 27.91429 18.05718 0 99 ve_forms | 102,197 1.793203 1.16216 1 37 road_fnc | 102,197 7.758466 6.135542 1 99 harm_ev | 102,197 14.87309 10.53124 1 99 man_coll | 102,197 1.662329 1.788939 0 9 -------------+--------------------------------------------------------- sch_bus | 102,197 .0054307 .0734932 0 1 veh_no | 102,197 1.326184 .8585167 0 37 make | 95,050 27.47883 22.02757 1 99 body_typ | 95,050 18.1325 21.64015 1 99 mod_year | 95,050 89.55787 5.982608 26 99 -------------+--------------------------------------------------------- rollover | 95,050 .3397054 .6951454 0 2 tow_veh | 95,050 .0907733 .6091118 0 9 spec_use | 95,050 .0429984 .5565504 0 9 emer_use | 95,050 .0020936 .0457086 0 1 impact1 | 95,050 10.70031 13.80066 0 99 -------------+--------------------------------------------------------- impact2 | 95,050 10.75533 13.94106 0 99 impacts | 95,050 1.200463 .6991305 0 9 fire_exp | 95,050 .0241662 .1535658 0 1 wgtcd_tr | 30,997 3.384166 3.100374 1 9 per_no | 102,197 1.743495 1.610473 1 42 -------------+--------------------------------------------------------- n_mot_no | 102,197 .0781921 .8603299 0 99 age | 102,197 36.76738 22.21942 0 99 sex | 102,197 1.466139 1.047952 1 9 per_typ | 102,197 1.673415 1.113557 1 19 seat_pos | 102,197 14.54674 13.45346 0 99 -------------+--------------------------------------------------------- location | 102,197 .7889566 3.643982 0 99 ejection | 102,197 .1857393 .743389 0 9 extricat | 102,197 .1866689 .995095 0 9 alc_det | 102,197 8.089513 2.329037 1 9 drinking | 102,197 4.358357 3.995485 0 9 -------------+--------------------------------------------------------- inj_sev | 102,197 2.577003 1.642584 0 9 hospital | 102,197 .7098154 1.189517 0 9 death_mo | 102,197 2.805875 4.438387 0 99 death_da | 102,197 6.496531 9.842522 0 99 death_yr | 102,197 39.87805 47.72928 0 99 -------------+--------------------------------------------------------- death_hr | 102,197 6.831257 14.91187 0 99 death_mn | 102,197 12.76103 21.44813 0 99 lag_hrs | 102,197 621.4831 478.0324 0 999 lag_mins | 102,197 67.92141 40.89728 0 99 p_cf1 | 102,197 .5567874 4.953288 0 99 -------------+--------------------------------------------------------- p_cf2 | 102,197 .3837686 4.562596 0 99 p_cf3 | 102,197 .1844281 3.739567 0 99 work_inj | 102,197 4.927698 3.907041 0 9 st_case | 102,197 275239.5 160557.5 10001 560118 mak_mod | 95,050 27763.84 22160.59 1001 99999 -------------+--------------------------------------------------------- vin_wgt | 66,703 3688.234 2398.629 93 9999 whlbs_sh | 91,726 1719.746 2269.238 109 9999 whlbs_lg | 91,726 968.5424 2544.343 0 9999 mcycl_ds | 5,907 6379.616 4463.748 49 9999 death_tm | 102,197 695.8868 1507.223 0 9999 -------------+--------------------------------------------------------- cert_no | 0 ser_tr | 0 vina_mod | 0 vin_bt | 0 rest_use | 102,197 10.79639 28.29169 0 99 -------------+--------------------------------------------------------- air_bag | 102,197 7.833635 2.726785 0 9 ej_path | 102,197 .9358787 2.671978 0 9 alc_res | 102,197 67.25386 42.47385 0 99 drugs | 102,197 6.658072 3.04677 0 9 drug_det | 102,197 7.766657 1.207139 1 8 -------------+--------------------------------------------------------- drugtst1 | 102,197 1.675812 3.25434 0 9 drugres1 | 102,197 181.7945 378.3631 0 999 drugtst2 | 102,197 .6807245 2.344685 0 9 drugres2 | 102,197 78.25302 264.2829 0 999 drugtst3 | 102,197 .6564478 2.327765 0 9 -------------+--------------------------------------------------------- drugres3 | 102,197 73.95227 260.3999 0 999 by Jean Roth , jroth@nber.org , 18 Apr 2016