Summary statistics for person dataset : by Jean Roth , jroth@nber.org , 18 Apr 2016 Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- state | 109,073 27.23377 16.10635 1 56 county | 109,073 86.86566 94.40294 0 997 month | 109,073 6.810476 3.282001 1 12 day | 109,073 15.83094 8.88153 1 99 hour | 109,073 13.51726 9.153843 0 99 -------------+--------------------------------------------------------- minute | 109,073 27.47603 18.0388 0 99 ve_forms | 109,073 1.715347 .9261161 1 24 road_fnc | 109,073 4.448626 2.158892 1 9 harm_ev | 109,073 14.85876 10.46027 1 99 man_coll | 109,073 1.527812 1.747916 0 9 -------------+--------------------------------------------------------- sch_bus | 109,073 .0044374 .0664661 0 1 veh_no | 109,073 1.274697 .7604676 0 24 make | 100,273 26.89731 21.73615 1 99 body_typ | 100,273 20.65255 25.45706 1 99 mod_year | 100,273 79.42063 5.995415 0 99 -------------+--------------------------------------------------------- rollover | 100,273 .3113002 .6719446 0 2 tow_veh | 100,273 .0851775 .5697123 0 9 spec_use | 100,273 .0491458 .5944048 0 9 emer_use | 100,273 .0017253 .041501 0 1 impact1 | 100,273 9.809051 12.29147 0 99 -------------+--------------------------------------------------------- impact2 | 100,273 9.931597 12.41892 0 99 impacts | 100,273 1.125647 .6223714 0 9 fire_exp | 100,273 .0301278 .1709396 0 1 wgtcd_tr | 35,951 4.350616 3.573615 0 9 per_no | 109,073 1.707205 1.60195 1 41 -------------+--------------------------------------------------------- n_mot_no | 109,073 .09644 1.073482 0 99 age | 109,073 34.40981 21.81952 0 99 sex | 109,073 1.473894 1.210203 1 9 per_typ | 109,073 1.705958 1.154677 1 9 seat_pos | 109,073 14.66754 14.9308 0 99 -------------+--------------------------------------------------------- man_rest | 109,073 2.323875 3.537158 0 9 aut_rest | 109,073 .2014706 1.33038 0 9 location | 109,073 .9125448 3.729871 0 99 ejection | 109,073 .1823274 .7425184 0 9 extricat | 109,073 .1020326 .7275154 0 9 -------------+--------------------------------------------------------- drinking | 109,073 4.008077 3.96995 0 9 test_res | 109,073 66.87461 41.78232 0 99 inj_sev | 109,073 2.617238 1.663559 0 9 hospital | 109,073 .6933155 1.064655 0 9 death_mo | 109,073 2.941094 4.842143 0 99 -------------+--------------------------------------------------------- death_da | 109,073 6.761976 10.12818 0 99 death_yr | 109,073 36.34137 42.48449 0 99 death_hr | 109,073 7.921346 17.92196 0 99 death_mn | 109,073 13.21476 22.69499 0 99 lag_hrs | 46,087 96.87252 270.4411 0 999 -------------+--------------------------------------------------------- lag_mins | 46,087 24.05661 28.29446 0 99 p_cf1 | 109,073 .5027734 4.557912 0 99 p_cf2 | 109,073 .2415538 3.947842 0 99 p_cf3 | 109,073 .1618732 3.663266 0 99 st_case | 109,073 273215.6 160857.7 10001 560150 -------------+--------------------------------------------------------- mak_mod | 100,273 2726.076 2187.649 101 9999 vin_wgt | 70,056 4086.31 2679.885 0 9999 whlbs_sh | 70,056 2403.715 3201.15 0 9999 whlbs_lg | 70,056 1633.716 3541.27 0 9999 mcycl_ds | 15,308 7095.102 4312.642 49 9999 -------------+--------------------------------------------------------- death_tm | 109,073 805.3494 1810.333 0 9999 vina_mod | 0 ser_tr | 0 vin_bt | 0 by Jean Roth , jroth@nber.org , 18 Apr 2016