Summary statistics for person dataset : by Jean Roth , jroth@nber.org , 18 Apr 2016 Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- state | 99,316 27.28362 16.02358 1 56 county | 99,316 86.3866 91.99355 1 997 month | 99,316 6.82163 3.307024 1 12 day | 99,316 15.6377 8.8921 1 99 hour | 99,316 13.29363 8.803066 0 99 -------------+--------------------------------------------------------- minute | 99,316 30.16334 22.6307 0 99 ve_forms | 99,316 1.686536 .9659315 1 22 road_fnc | 99,316 4.440392 2.164112 1 9 harm_ev | 99,316 14.67062 10.35015 1 99 man_coll | 99,316 1.462594 1.717482 0 9 -------------+--------------------------------------------------------- sch_bus | 99,316 .0056184 .0747457 0 1 veh_no | 99,316 1.254984 .7758032 0 22 make | 90,673 27.10957 22.76823 1 99 body_typ | 90,673 20.20213 25.14352 1 99 mod_year | 90,673 76.59546 5.798463 9 99 -------------+--------------------------------------------------------- rollover | 90,673 .3019532 .6628438 0 9 tow_veh | 90,673 .4468254 1.833223 0 9 spec_use | 90,673 .4399656 1.913147 0 9 emer_use | 90,673 .0021616 .0464431 0 1 impact1 | 90,673 9.495252 11.0744 0 99 -------------+--------------------------------------------------------- impact2 | 90,673 13.281 20.92014 0 99 impacts | 90,673 1.119352 .6453979 0 9 fire_exp | 90,673 .0256636 .1582701 0 2 wgtcd_tr | 34,481 5.149851 3.682193 0 9 per_no | 99,316 1.738864 1.883573 1 50 -------------+--------------------------------------------------------- n_mot_no | 99,316 .0914656 .6161099 0 99 age | 99,316 33.93584 21.22757 0 99 sex | 99,316 1.422611 1.045288 1 9 per_typ | 99,316 1.727224 1.180013 1 9 seat_pos | 99,316 14.57456 15.07023 0 99 -------------+--------------------------------------------------------- man_rest | 99,316 1.986951 3.604392 0 9 aut_rest | 99,316 .2600387 1.506776 0 9 location | 99,316 1.045874 4.688106 0 99 ejection | 99,316 .2762999 1.16996 0 9 extricat | 99,316 .1327077 .8602431 0 9 -------------+--------------------------------------------------------- drinking | 99,316 4.158403 3.972488 0 9 test_res | 99,316 73.8433 38.35302 0 99 inj_sev | 99,316 2.609378 1.650951 0 9 hospital | 99,316 .7439285 1.180961 0 9 death_mo | 99,316 3.034335 5.222208 0 99 -------------+--------------------------------------------------------- death_da | 99,316 6.812749 10.21319 0 99 death_yr | 99,316 35.59419 41.07889 0 84 death_hr | 99,316 8.994704 20.51756 0 99 death_mn | 99,316 14.32917 24.54074 0 99 lag_hrs | 42,589 123.2221 305.9374 0 999 -------------+--------------------------------------------------------- lag_mins | 42,589 28.33358 33.61477 0 99 p_cf1 | 99,316 .4885215 4.530652 0 99 p_cf2 | 99,316 .2550042 4.0787 0 99 p_cf3 | 99,316 .1761448 3.855888 0 99 st_case | 99,316 273631.7 160090.7 10001 560152 -------------+--------------------------------------------------------- mak_mod | 90,673 2746.66 2291.05 101 9999 vin_wgt | 66,531 4612.206 2966.292 0 9999 whlbs_sh | 66,532 3005.64 3680.233 0 9999 whlbs_lg | 66,532 2321.577 4056.069 0 9999 mcycl_ds | 18,485 7959.874 3850.809 49 9999 -------------+--------------------------------------------------------- death_tm | 99,316 913.7995 2072.152 0 9999 vina_mod | 0 ser_tr | 0 vin_bt | 0 by Jean Roth , jroth@nber.org , 18 Apr 2016