Summary statistics for person dataset : by Jean Roth , jroth@nber.org , 18 Apr 2016 Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- state | 111,457 27.07763 16.05098 1 56 county | 111,457 84.99485 92.37087 1 997 month | 111,457 6.844999 3.318118 1 12 day | 111,457 15.65397 8.835477 1 99 hour | 111,457 13.57791 9.13161 0 99 -------------+--------------------------------------------------------- minute | 111,457 27.66459 17.99922 0 99 ve_forms | 111,457 1.750361 1.069413 1 22 road_fnc | 111,457 7.880008 5.987283 1 99 harm_ev | 111,457 14.69111 10.34264 1 99 man_coll | 111,457 1.546004 1.754011 0 9 -------------+--------------------------------------------------------- sch_bus | 111,457 .0064778 .0802242 0 1 veh_no | 111,457 1.295181 .8192749 0 22 make | 102,644 27.016 21.77524 1 99 body_typ | 102,644 21.0028 25.33446 1 99 mod_year | 102,644 80.4934 5.963207 15 99 -------------+--------------------------------------------------------- rollover | 102,644 .3153618 .6732587 0 2 tow_veh | 102,644 .0808815 .5512829 0 9 spec_use | 102,644 .0455847 .5708966 0 9 emer_use | 102,644 .0019095 .0436564 0 1 impact1 | 102,644 9.921807 12.61573 0 99 -------------+--------------------------------------------------------- impact2 | 102,644 10.03505 12.82352 0 99 impacts | 102,644 1.135692 .6555328 0 9 fire_exp | 102,644 .0271326 .1624706 0 1 wgtcd_tr | 34,300 4.344344 3.566301 0 9 per_no | 111,457 1.713926 1.565678 1 47 -------------+--------------------------------------------------------- n_mot_no | 111,457 .0822918 .5029986 0 99 age | 111,457 34.53489 21.74384 0 99 sex | 111,457 1.46941 1.170045 1 9 per_typ | 111,457 1.703141 1.148041 1 9 seat_pos | 111,457 14.67401 14.76937 0 99 -------------+--------------------------------------------------------- man_rest | 111,457 2.264936 3.391855 0 9 aut_rest | 111,457 .1926483 1.300796 0 9 location | 111,457 .8983913 3.710596 0 99 ejection | 111,457 .191787 .7738478 0 9 extricat | 111,457 .1263267 .8223508 0 9 -------------+--------------------------------------------------------- alc_det | 111,457 7.783369 2.672727 1 9 drinking | 111,457 4.255623 3.95645 0 9 test_res | 111,457 66.4465 42.04072 0 99 toxclgy | 111,457 2.186601 3.296914 0 9 inj_sev | 111,457 2.589115 1.647181 0 9 -------------+--------------------------------------------------------- hospital | 111,457 .6770055 1.016499 0 9 death_mo | 111,457 3.10535 6.490906 0 99 death_da | 111,457 6.790924 10.84553 0 99 death_yr | 111,457 36.21311 42.88813 0 99 death_hr | 111,457 7.492629 16.97445 0 99 -------------+--------------------------------------------------------- death_mn | 111,457 12.94947 22.19246 0 99 lag_hrs | 46,390 88.9604 257.7541 0 999 lag_mins | 46,390 24.22895 27.45584 0 99 p_cf1 | 111,457 .4857927 4.58423 0 99 p_cf2 | 111,457 .2577496 4.097393 0 99 -------------+--------------------------------------------------------- p_cf3 | 111,457 .1684237 3.773394 0 99 work_inj | 111,457 5.323129 3.851909 0 9 st_case | 111,457 271667.1 160255.1 10001 560114 mak_mod | 102,644 2749.957 2188.336 101 9999 vin_wgt | 73,740 3983.558 2607.801 0 9999 -------------+--------------------------------------------------------- whlbs_sh | 73,740 2228.92 3027.381 0 9999 whlbs_lg | 73,740 1433.424 3352.642 0 9999 mcycl_ds | 13,997 7155.633 4280.062 49 9999 death_tm | 111,457 762.2124 1714.834 0 9999 ser_tr | 0 -------------+--------------------------------------------------------- vina_mod | 0 vin_bt | 0 by Jean Roth , jroth@nber.org , 18 Apr 2016