Summary statistics for person dataset : by Jean Roth , jroth@nber.org , 18 Apr 2016 Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- state | 104,045 27.33851 16.08907 1 56 county | 104,045 86.78045 95.09297 1 997 month | 104,045 6.776395 3.293201 1 12 day | 104,045 15.75681 8.87755 1 99 hour | 104,045 13.50911 8.953576 0 99 -------------+--------------------------------------------------------- minute | 104,045 27.4091 18.12397 0 99 ve_forms | 104,045 1.767408 1.491712 1 36 road_fnc | 104,045 4.414196 2.162489 1 9 harm_ev | 104,045 14.63142 10.15986 1 99 man_coll | 104,045 1.524994 1.725764 0 9 -------------+--------------------------------------------------------- sch_bus | 104,045 .0070066 .083412 0 1 veh_no | 104,045 1.299822 1.011335 0 36 make | 95,482 27.44333 22.45826 1 99 body_typ | 95,482 21.11638 25.84966 1 99 mod_year | 95,482 78.62899 6.042481 9 99 -------------+--------------------------------------------------------- rollover | 95,482 .2945058 .6580212 0 2 tow_veh | 95,482 .0899646 .579091 0 9 spec_use | 95,482 .0484803 .5858641 0 9 emer_use | 95,482 .0019585 .0442116 0 1 impact1 | 95,482 9.595337 11.27337 0 99 -------------+--------------------------------------------------------- impact2 | 95,482 9.877097 11.88801 0 99 impacts | 95,482 1.136968 .6027479 0 9 fire_exp | 95,482 .0247795 .1554534 0 1 wgtcd_tr | 32,765 4.980955 3.652657 0 9 per_no | 104,045 1.741794 2.073308 1 75 -------------+--------------------------------------------------------- n_mot_no | 104,044 .0982181 1.195271 0 99 age | 104,045 34.63865 21.82031 0 99 sex | 104,045 1.470143 1.188375 1 9 per_typ | 104,045 1.704791 1.151301 1 9 seat_pos | 104,045 15.04359 15.92184 0 99 -------------+--------------------------------------------------------- man_rest | 104,045 2.266683 3.635032 0 9 aut_rest | 104,045 .2301985 1.420336 0 9 location | 104,045 .9173723 3.751286 0 99 ejection | 104,045 .173771 .7202256 0 9 extricat | 104,045 .1013023 .711026 0 9 -------------+--------------------------------------------------------- drinking | 104,045 3.984113 3.979423 0 9 test_res | 104,045 68.19053 41.36094 0 99 inj_sev | 104,045 2.601788 1.675576 0 9 hospital | 104,045 .7252919 1.164303 0 9 death_mo | 104,045 2.959892 5.140664 0 99 -------------+--------------------------------------------------------- death_da | 104,045 6.809506 10.46817 0 99 death_yr | 104,045 35.80754 41.9732 0 99 death_hr | 104,045 8.2492 18.78243 0 99 death_mn | 104,045 13.49374 23.28789 0 99 lag_hrs | 43,825 106.2296 283.3767 0 999 -------------+--------------------------------------------------------- lag_mins | 43,825 24.59726 29.13542 0 99 p_cf1 | 104,045 .4911048 4.591124 0 99 p_cf2 | 104,045 .251843 4.117348 0 99 p_cf3 | 104,045 .181162 3.903947 0 99 st_case | 104,045 274234.3 160711.5 10002 560136 -------------+--------------------------------------------------------- mak_mod | 95,482 2781.47 2260.576 101 9999 vin_wgt | 70,233 4308.313 2826.204 0 9999 whlbs_sh | 70,233 2611.696 3392.969 0 9999 whlbs_lg | 70,233 1879.195 3744.829 0 9999 mcycl_ds | 16,876 7444.264 4151.33 49 9999 -------------+--------------------------------------------------------- death_tm | 104,045 838.4137 1897.154 0 9999 vina_mod | 0 ser_tr | 0 vin_bt | 0 by Jean Roth , jroth@nber.org , 18 Apr 2016