Summary statistics for person dataset : by Jean Roth , jroth@nber.org , 22 Apr 2016 Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- state | 111,108 28.11669 15.85172 1 56 county | 111,108 86.09837 91.41024 1 999 month | 111,108 6.904768 3.278227 1 99 day | 111,108 15.63943 8.867522 1 99 hour | 111,108 13.30933 8.224234 0 99 -------------+--------------------------------------------------------- minute | 111,108 26.94523 17.68845 0 99 ve_forms | 111,108 1.671437 .9631602 0 28 road_fnc | 0 harm_ev | 111,108 12.74769 6.799633 1 99 man_coll | 111,108 1.612449 1.895798 0 9 -------------+--------------------------------------------------------- sch_bus | 111,108 .0075422 .0865182 0 1 veh_no | 111,108 1.249217 .7702094 0 28 make | 101,368 25.23005 22.3105 1 99 body_typ | 101,368 17.24696 22.89845 1 99 mod_year | 101,368 71.79203 5.696223 0 99 -------------+--------------------------------------------------------- rollover | 0 tow_veh | 101,368 .0093915 .0964542 0 1 spec_use | 101,368 .0206969 .3268115 0 9 emer_use | 101,368 .0016179 .0401904 0 1 impact1 | 101,368 9.897788 11.37492 0 99 -------------+--------------------------------------------------------- impact2 | 101,368 10.58408 13.30402 0 99 impacts | 101,368 1.175114 .6354879 0 9 fire_exp | 101,368 .0249783 .158319 0 9 wgtcd_tr | 51,748 6.776185 3.416829 0 9 per_no | 111,108 1.73875 1.664411 1 44 -------------+--------------------------------------------------------- age | 111,108 31.70787 19.62424 0 99 sex | 111,108 1.299348 .4919329 1 9 per_typ | 111,108 1.572812 .7611156 1 9 seat_pos | 111,108 5.987076 19.38327 0 99 man_rest | 111,108 2.453568 3.911605 0 9 -------------+--------------------------------------------------------- aut_rest | 111,108 .3674353 1.780139 0 9 location | 111,108 .7684685 3.325589 0 99 ejection | 111,108 .3379955 1.363125 0 9 extricat | 111,108 .6017208 2.130258 0 9 drinking | 111,108 .178655 .3830649 0 1 -------------+--------------------------------------------------------- test_res | 111,108 80.69648 34.05681 0 99 inj_sev | 111,108 2.647811 1.536396 0 9 hospital | 111,108 1.038935 1.735437 0 9 death_mo | 111,108 3.020656 4.568616 0 99 death_da | 111,108 6.882574 10.4283 0 99 -------------+--------------------------------------------------------- death_yr | 111,108 33.18804 38.14061 0 99 death_hr | 111,108 9.561661 21.63047 0 99 death_mn | 111,108 14.74872 25.23749 0 99 lag_hrs | 47,879 136.3163 322.3602 0 999 lag_mins | 47,879 27.15587 31.27638 0 99 -------------+--------------------------------------------------------- p_cf1 | 111,108 1.128173 9.141377 0 99 p_cf2 | 111,108 .8780826 8.976674 0 99 p_cf3 | 111,108 .8142528 8.903945 0 99 st_case | 111,108 282282 158185.7 10001 560208 mak_mod | 101,368 2559.056 2244.9 100 9999 -------------+--------------------------------------------------------- vin_wgt | 82,977 5890.056 3314.117 0 9999 whlbs_sh | 82,977 4525.853 4324.252 0 9999 whlbs_lg | 82,977 4008.463 4747.232 0 9999 mcycl_ds | 34,993 9520.981 1732.853 0 9999 death_tm | 111,108 970.9148 2184.438 0 9999 -------------+--------------------------------------------------------- vina_mod | 0 ser_tr | 0 by Jean Roth , jroth@nber.org , 22 Apr 2016