Summary statistics for person dataset : by Jean Roth , jroth@nber.org , 18 Apr 2016 Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- state | 109,866 26.98866 16.1109 1 56 county | 109,866 85.87577 91.41592 0 999 month | 109,866 6.76505 3.362505 1 12 day | 109,866 15.65588 8.853424 1 99 hour | 109,866 13.47144 8.769979 0 99 -------------+--------------------------------------------------------- minute | 109,866 27.48399 17.98153 0 99 ve_forms | 109,866 1.774325 1.455524 1 43 road_fnc | 109,866 7.90563 5.697053 1 99 harm_ev | 109,866 14.66925 10.29053 1 99 man_coll | 109,866 1.58382 1.773038 0 9 -------------+--------------------------------------------------------- sch_bus | 109,866 .0057525 .0756269 0 1 veh_no | 109,866 1.310815 1.021002 0 43 make | 101,401 26.95892 21.36298 1 99 body_typ | 101,401 21.78297 25.56745 1 99 mod_year | 101,401 82.43893 5.944601 22 99 -------------+--------------------------------------------------------- rollover | 101,401 .3145531 .6715478 0 2 tow_veh | 101,401 .0880465 .6091343 0 9 spec_use | 101,401 .0507786 .6145952 0 9 emer_use | 101,401 .0018146 .0425594 0 1 impact1 | 101,401 10.54457 13.96831 0 99 -------------+--------------------------------------------------------- impact2 | 101,401 10.49529 13.93352 0 99 impacts | 101,401 1.163332 .6273429 0 9 fire_exp | 101,401 .0254928 .1576173 0 1 wgtcd_tr | 33,418 4.029804 3.481595 1 9 per_no | 109,866 1.770457 2.220019 1 82 -------------+--------------------------------------------------------- n_mot_no | 109,866 .0800248 .4300464 0 99 age | 109,866 35.08493 21.79533 0 99 sex | 109,866 1.461963 1.112616 1 9 per_typ | 109,866 1.694874 1.126392 1 9 seat_pos | 109,866 14.43103 13.81721 0 99 -------------+--------------------------------------------------------- man_rest | 109,866 2.233448 3.255803 0 9 aut_rest | 109,866 1.659139 3.487899 0 9 location | 109,866 .8636157 3.602904 0 99 ejection | 109,866 .2033659 .8216188 0 9 extricat | 109,866 .2441429 1.299449 0 9 -------------+--------------------------------------------------------- alc_det | 109,866 7.953143 2.505587 1 9 drinking | 109,866 4.447491 3.957499 0 9 test_res | 109,866 65.45216 42.50879 0 99 toxclgy | 109,866 2.223809 3.284512 0 9 inj_sev | 109,866 2.60288 1.652239 0 9 -------------+--------------------------------------------------------- hospital | 109,866 .7907906 1.379173 0 9 death_mo | 109,866 2.845776 4.515873 0 99 death_da | 109,866 6.552983 9.846585 0 99 death_yr | 109,866 36.92649 43.85259 0 99 death_hr | 109,866 7.514154 17.04336 0 99 -------------+--------------------------------------------------------- death_mn | 109,866 12.89522 22.16301 0 99 lag_hrs | 45,582 89.47688 259.3151 0 999 lag_mins | 45,582 24.07661 27.5131 0 99 p_cf1 | 109,866 .4535707 4.332658 0 99 p_cf2 | 109,866 .2315184 3.827469 0 99 -------------+--------------------------------------------------------- p_cf3 | 109,866 .1446034 3.481366 0 99 work_inj | 109,866 5.121457 3.885002 0 9 st_case | 109,866 270782.8 160854.9 10001 560114 mak_mod | 101,401 2743.805 2146.781 101 9999 vin_wgt | 72,243 3871.411 2536.423 1444 9999 -------------+--------------------------------------------------------- whlbs_sh | 72,248 2018.673 2786.75 798 9999 whlbs_lg | 72,248 1172.677 3095.162 0 9999 mcycl_ds | 11,150 7180.209 4259.576 49 9999 death_tm | 109,866 764.3106 1721.829 0 9999 ser_tr | 0 -------------+--------------------------------------------------------- vina_mod | 0 vin_bt | 0 by Jean Roth , jroth@nber.org , 18 Apr 2016