Summary statistics for person dataset : by Jean Roth , jroth@nber.org , 18 Apr 2016 Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- state | 1,416 43 0 43 43 county | 1,416 72 0 72 72 month | 1,416 6.840395 3.563848 1 12 day | 1,416 15.32415 9.297753 1 31 hour | 1,416 13.14619 7.623598 0 24 -------------+--------------------------------------------------------- minute | 1,416 24.19703 16.83338 0 58 ve_forms | 1,416 1.624294 .6983698 1 4 road_fnc | 1,416 9.492938 5.137951 1 16 harm_ev | 1,416 14.50141 9.597408 1 43 man_coll | 1,416 1.34322 1.748739 0 6 -------------+--------------------------------------------------------- sch_bus | 1,416 .0014124 .037569 0 1 veh_no | 1,416 1.15113 .7451412 0 4 make | 1,170 37.62821 22.60709 2 99 body_typ | 1,170 16.14615 26.84541 2 99 mod_year | 1,170 87.88974 6.783766 64 99 -------------+--------------------------------------------------------- rollover | 1,170 .117094 .4577609 0 2 tow_veh | 1,170 .3923077 1.83841 0 9 spec_use | 1,170 .4042735 1.858506 0 9 emer_use | 1,170 0 0 0 0 impact1 | 1,170 9.059829 4.007245 0 13 -------------+--------------------------------------------------------- impact2 | 1,170 9.283761 3.986482 0 13 impacts | 1,170 1.287179 .5845953 0 3 fire_exp | 1,170 .0153846 .1231296 0 1 wgtcd_tr | 301 5.096346 3.696037 1 9 per_no | 1,416 1.528955 1.11235 1 13 -------------+--------------------------------------------------------- n_mot_no | 1,416 .1765537 .3923847 0 3 age | 1,416 39.24364 23.70652 0 99 sex | 1,416 1.50565 1.452658 1 9 per_typ | 1,416 1.991525 1.496261 1 8 seat_pos | 1,416 10.83333 6.552569 0 52 -------------+--------------------------------------------------------- location | 1,416 2.346045 5.164053 0 18 ejection | 1,416 .3269774 1.616087 0 9 extricat | 1,416 .2987288 1.61281 0 9 alc_det | 1,416 7.431497 3.00851 1 9 drinking | 1,416 6.348164 3.167565 0 8 -------------+--------------------------------------------------------- inj_sev | 1,416 2.593927 1.55136 0 4 hospital | 1,416 .5233051 .499633 0 1 death_mo | 1,416 2.894774 4.099411 0 12 death_da | 1,416 6.409605 9.51348 0 31 death_yr | 1,416 40.74647 47.46626 0 97 -------------+--------------------------------------------------------- death_hr | 1,416 5.638418 9.713888 0 99 death_mn | 1,416 10.12853 16.72016 0 99 lag_hrs | 1,416 590.779 482.9344 0 999 lag_mins | 1,416 60.80014 45.90792 0 99 p_cf1 | 1,416 .0409605 .3543015 0 4 -------------+--------------------------------------------------------- p_cf2 | 1,416 .0628531 .5457229 0 5 p_cf3 | 1,416 .0035311 .1328735 0 5 work_inj | 1,416 4.606638 3.953251 0 8 st_case | 1,416 430279 159.3805 430001 430553 mak_mod | 1,170 37863.86 22721.52 2402 99999 -------------+--------------------------------------------------------- vin_wgt | 949 4403.519 3339.832 137 9999 whlbs_sh | 1,100 2220.789 3035.326 799 9999 whlbs_lg | 1,100 1482.927 3356.398 0 9999 mcycl_ds | 146 8604.562 3323.896 49 9999 death_tm | 1,416 573.9703 981.5414 0 9999 -------------+--------------------------------------------------------- cert_no | 0 ser_tr | 0 vina_mod | 0 vin_bt | 0 rest_use | 1,416 4.175141 17.62556 0 99 -------------+--------------------------------------------------------- air_bag | 1,416 7.436441 3.41109 0 9 ej_path | 1,416 .3269774 1.616087 0 9 alc_res | 1,416 45.01836 45.42406 0 97 drugs | 1,416 8 0 8 8 drug_det | 1,416 8 0 8 8 -------------+--------------------------------------------------------- drugtst1 | 1,416 .3573446 .4793868 0 1 drugres1 | 1,416 17.04873 87.02143 0 695 drugtst2 | 1,416 .0169492 .1291265 0 1 drugres2 | 1,416 6.900424 59.82733 0 695 drugtst3 | 1,416 .0042373 .0649793 0 1 -------------+--------------------------------------------------------- drugres3 | 1,416 2.302966 38.04716 0 695 by Jean Roth , jroth@nber.org , 18 Apr 2016