Summary statistics for person dataset : by Jean Roth , jroth@nber.org , 18 Apr 2016 Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- state | 1,318 43 0 43 43 county | 1,318 72 0 72 72 month | 1,318 6.569803 3.508648 1 12 day | 1,318 16.14795 8.745284 1 31 hour | 1,318 14.61533 10.15558 0 99 -------------+--------------------------------------------------------- minute | 1,318 23.86267 18.78771 0 99 ve_forms | 1,318 1.49393 .6564044 1 3 road_fnc | 1,318 5.000759 2.344479 2 8 harm_ev | 1,318 14.90516 10.71737 1 44 man_coll | 1,318 1.037178 1.643001 0 6 -------------+--------------------------------------------------------- sch_bus | 1,318 .0409712 .1982987 0 1 veh_no | 1,318 1.040212 .7073047 0 3 make | 1,045 32.04019 23.46976 1 99 body_typ | 1,045 17.06507 26.73887 2 99 mod_year | 1,045 76.68708 7.388681 61 99 -------------+--------------------------------------------------------- rollover | 1,045 .2909091 .6833849 0 2 tow_veh | 1,045 .3779904 1.789094 0 9 spec_use | 1,045 .4698565 1.71267 0 9 emer_use | 1,045 .0038278 .0617799 0 1 impact1 | 1,045 14.11579 20.61281 0 99 -------------+--------------------------------------------------------- impact2 | 1,045 14.10622 20.43374 0 99 impacts | 1,045 1.048804 .7469677 0 9 fire_exp | 1,045 .0095694 .0974006 0 1 wgtcd_tr | 733 8.360164 2.093745 1 9 per_no | 1,318 2.592564 5.812053 1 52 -------------+--------------------------------------------------------- n_mot_no | 1,318 .2867982 2.754108 0 99 age | 1,318 38.51897 24.7435 0 99 sex | 1,318 1.623672 1.719366 1 9 per_typ | 1,318 2.160091 1.571196 1 8 seat_pos | 1,318 27.09408 35.82112 0 99 -------------+--------------------------------------------------------- man_rest | 1,318 .560698 1.95753 0 9 aut_rest | 1,318 .3482549 1.736462 0 9 location | 1,318 3.197269 10.43753 0 99 ejection | 1,318 .0128983 .1128788 0 1 extricat | 1,318 .0091047 .0950193 0 1 -------------+--------------------------------------------------------- drinking | 1,318 2.176783 3.552813 0 9 test_res | 1,318 66.16995 41.81648 0 99 inj_sev | 1,318 2.415023 1.589636 0 9 hospital | 1,318 .5811836 .4935525 0 1 death_mo | 1,318 2.594082 3.926608 0 12 -------------+--------------------------------------------------------- death_da | 1,318 6.450683 9.851143 0 31 death_yr | 1,318 32.3695 40.49929 0 84 death_hr | 1,318 5.834598 11.82766 0 99 death_mn | 1,318 9.518209 17.59908 0 99 lag_hrs | 514 57.50584 188.9325 0 999 -------------+--------------------------------------------------------- lag_mins | 514 12.54669 21.17473 0 99 p_cf1 | 1,318 2.660091 14.4663 0 99 p_cf2 | 1,318 2.163126 14.28891 0 99 p_cf3 | 1,318 2.103187 14.281 0 99 st_case | 1,318 430240.8 141.4274 430001 430494 -------------+--------------------------------------------------------- mak_mod | 1,045 3266.92 2338.284 101 9900 vin_wgt | 973 7781.876 3442.111 1610 9999 whlbs_sh | 973 7212.098 4166.561 866 9999 whlbs_lg | 973 6938.02 4579.468 0 9999 mcycl_ds | 675 9897.676 990.6393 72 9999 -------------+--------------------------------------------------------- death_tm | 1,318 592.978 1194.974 0 9999 vina_mod | 0 ser_tr | 0 vin_bt | 0 by Jean Roth , jroth@nber.org , 18 Apr 2016