Summary statistics for person dataset : by Jean Roth , jroth@nber.org , 18 Apr 2016 Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- state | 1,486 43 0 43 43 county | 1,486 72 0 72 72 month | 1,486 6.462315 3.436327 1 12 day | 1,486 15.04643 8.844553 1 31 hour | 1,486 12.54441 7.452953 0 24 -------------+--------------------------------------------------------- minute | 1,486 24.14536 16.51235 0 55 ve_forms | 1,486 1.694482 .8759006 1 5 road_fnc | 1,486 9.356662 4.984351 1 16 harm_ev | 1,486 14.96097 9.982265 1 43 man_coll | 1,486 1.368775 1.735335 0 6 -------------+--------------------------------------------------------- sch_bus | 1,486 0 0 0 0 veh_no | 1,486 1.176985 .7890039 0 5 make | 1,247 36.56856 21.03665 2 99 body_typ | 1,247 14.79711 25.24429 2 99 mod_year | 1,247 86.25742 6.138736 64 99 -------------+--------------------------------------------------------- rollover | 1,247 .1010425 .4214062 0 2 tow_veh | 1,247 .3199679 1.662863 0 9 spec_use | 1,247 .3247795 1.66627 0 9 emer_use | 1,247 0 0 0 0 impact1 | 1,247 9.070569 4.069204 0 12 -------------+--------------------------------------------------------- impact2 | 1,247 9.092221 4.147404 0 13 impacts | 1,247 1.256616 .6022183 0 3 fire_exp | 1,247 .0088212 .0935434 0 1 wgtcd_tr | 278 5.248201 3.681289 1 9 per_no | 1,486 1.683715 1.600788 1 20 -------------+--------------------------------------------------------- n_mot_no | 1,486 .1608345 .3675019 0 1 age | 1,486 38.91588 24.26621 0 99 sex | 1,486 1.479139 1.395243 1 9 per_typ | 1,486 1.977793 1.452796 1 8 seat_pos | 1,486 11.55316 7.361072 0 55 -------------+--------------------------------------------------------- location | 1,486 2.114401 4.877665 0 18 ejection | 1,486 .2907133 1.545366 0 9 extricat | 1,486 .2725437 1.542795 0 9 alc_det | 1,486 7.561911 2.922547 1 9 drinking | 1,486 6.477793 3.079067 0 8 -------------+--------------------------------------------------------- inj_sev | 1,486 2.569987 1.510952 0 4 hospital | 1,486 .5720054 .4949546 0 1 death_mo | 1,486 2.644011 3.929743 0 12 death_da | 1,486 6.090175 9.274632 0 31 death_yr | 1,486 37.83042 46.11513 0 95 -------------+--------------------------------------------------------- death_hr | 1,486 4.968371 8.037853 0 99 death_mn | 1,486 10.21198 16.5569 0 99 lag_hrs | 1,486 607.3096 480.3241 0 999 lag_mins | 1,486 63.893 44.30467 0 99 p_cf1 | 1,486 .1110363 2.397906 0 90 -------------+--------------------------------------------------------- p_cf2 | 1,486 .0632571 .5565973 0 5 p_cf3 | 1,486 0 0 0 0 work_inj | 1,486 4.780619 3.924411 0 8 st_case | 1,486 430272.1 159.225 430001 430550 mak_mod | 1,247 36890.97 21105.17 2402 99999 -------------+--------------------------------------------------------- vin_wgt | 1,041 4311.687 3278.376 216 9999 whlbs_sh | 1,177 2199.855 3040.456 799 9999 whlbs_lg | 1,177 1468.418 3356.211 0 9999 mcycl_ds | 143 8260.259 3619.432 171 9999 death_tm | 1,486 507.0491 813.8853 0 9999 -------------+--------------------------------------------------------- cert_no | 0 ser_tr | 0 vina_mod | 0 vin_bt | 0 rest_use | 1,486 3.942127 16.85703 0 99 -------------+--------------------------------------------------------- air_bag | 1,486 7.55249 3.307517 0 9 ej_path | 1,486 .2907133 1.545366 0 9 alc_res | 1,486 49.77793 45.63263 0 97 drugs | 1,486 7.994616 .2075299 0 8 drug_det | 1,486 7.995289 .1815886 1 8 -------------+--------------------------------------------------------- drugtst1 | 1,486 .320996 .4670164 0 1 drugres1 | 1,486 24.54711 104.4168 0 695 drugtst2 | 1,486 .0188425 .1360145 0 1 drugres2 | 1,486 7.390983 61.32244 0 695 drugtst3 | 1,486 .0020188 .0449013 0 1 -------------+--------------------------------------------------------- drugres3 | 1,486 1.061238 25.94147 0 695 by Jean Roth , jroth@nber.org , 18 Apr 2016