Summary statistics for person dataset : by Jean Roth , jroth@nber.org , 18 Apr 2016 Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- state | 97,589 27.17795 16.11709 1 56 county | 97,589 87.09988 91.50208 0 999 month | 97,589 6.820543 3.314533 1 12 day | 97,589 15.62649 8.867921 1 99 hour | 97,589 13.41433 8.589371 0 99 -------------+--------------------------------------------------------- minute | 97,589 27.88091 17.93747 0 99 ve_forms | 97,589 1.760936 1.034742 1 22 road_fnc | 97,589 8.4691 9.089164 1 99 harm_ev | 97,589 14.73358 10.34305 1 99 man_coll | 97,589 1.587382 1.760627 0 9 -------------+--------------------------------------------------------- sch_bus | 97,589 .0061175 .0779752 0 1 veh_no | 97,589 1.30235 .7959585 0 22 make | 90,150 27.36302 21.93634 1 99 body_typ | 90,150 17.94402 22.61003 1 99 mod_year | 90,150 85.67573 6.017064 0 99 -------------+--------------------------------------------------------- rollover | 90,150 .3221409 .6808543 0 2 tow_veh | 90,150 .0877316 .611822 0 9 spec_use | 90,150 .0512368 .5949379 0 9 emer_use | 90,150 .0016972 .041162 0 1 impact1 | 90,150 10.13424 12.42408 0 99 -------------+--------------------------------------------------------- impact2 | 90,150 10.2461 12.66584 0 99 impacts | 90,150 1.177127 .6482885 0 9 fire_exp | 90,150 .0265446 .1607492 0 1 wgtcd_tr | 29,721 3.978063 3.441042 1 9 per_no | 97,589 1.76856 1.829827 1 52 -------------+--------------------------------------------------------- n_mot_no | 97,589 .0840054 .8233121 0 99 age | 97,589 36.1136 22.24987 0 99 sex | 97,589 1.467378 1.099273 1 9 per_typ | 97,589 1.696984 1.128278 1 9 seat_pos | 97,589 14.41997 13.36275 0 99 -------------+--------------------------------------------------------- location | 97,589 .8495527 3.497795 0 99 ejection | 97,589 .1746508 .6871248 0 9 extricat | 97,589 .1990491 1.114681 0 9 alc_det | 97,589 8.114634 2.334721 1 9 drinking | 97,589 4.477626 3.961035 0 9 -------------+--------------------------------------------------------- inj_sev | 97,589 2.581951 1.642582 0 9 hospital | 97,589 .8003156 1.419117 0 9 death_mo | 97,589 2.89341 4.953513 0 99 death_da | 97,589 6.551056 10.05655 0 99 death_yr | 97,589 38.26319 45.76613 0 99 -------------+--------------------------------------------------------- death_hr | 97,589 7.157026 16.15634 0 99 death_mn | 97,589 13.00866 22.04341 0 99 lag_hrs | 40,150 82.58869 247.3792 0 999 lag_mins | 40,150 23.57524 27.34801 0 99 p_cf1 | 97,589 .45251 4.426159 0 99 -------------+--------------------------------------------------------- p_cf2 | 97,589 .2370861 3.901899 0 99 p_cf3 | 97,589 .1326174 3.405584 0 99 work_inj | 97,589 5.03234 3.895321 0 9 st_case | 97,589 272512.7 161025.8 10001 560101 mak_mod | 90,150 27641.48 22080.24 1001 99999 -------------+--------------------------------------------------------- vin_wgt | 64,109 3982.329 2634.572 1085 9999 whlbs_sh | 64,109 1960.19 2713.282 798 9999 whlbs_lg | 64,109 1070.454 3021.029 0 9999 mcycl_ds | 9,127 7321.262 4177.47 49 9999 death_tm | 97,589 728.7112 1632.558 0 9999 -------------+--------------------------------------------------------- cert_no | 0 ser_tr | 0 vina_mod | 0 vin_bt | 0 rest_use | 97,589 2.428061 3.101718 0 9 -------------+--------------------------------------------------------- air_bag | 97,589 8.226952 2.467603 0 9 ej_path | 97,589 .9423398 2.685856 0 9 alc_res | 97,589 66.59322 42.41681 0 99 drugs | 97,589 6.901075 2.829052 0 9 drug_det | 97,589 7.879341 .8868557 1 8 -------------+--------------------------------------------------------- drugtst1 | 97,589 1.780908 3.358724 0 9 drugres1 | 97,589 189.4071 385.9827 0 999 drugtst2 | 97,589 .9932574 2.793727 0 9 drugres2 | 97,589 112.4999 313.42 0 999 drugtst3 | 97,589 .980797 2.791552 0 9 -------------+--------------------------------------------------------- drugres3 | 97,589 109.5674 311.4583 0 999 by Jean Roth , jroth@nber.org , 18 Apr 2016