Summary statistics for person dataset : by Jean Roth , jroth@nber.org , 18 Apr 2016 Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- state | 98,945 26.8615 16.13865 1 56 county | 98,945 86.94235 90.71062 0 999 month | 98,945 6.821325 3.339562 1 12 day | 98,945 15.66574 8.904824 1 99 hour | 98,945 13.45594 8.782397 0 99 -------------+--------------------------------------------------------- minute | 98,945 27.75861 18.05577 0 99 ve_forms | 98,945 1.758159 .8716206 1 15 road_fnc | 98,945 7.921633 6.184041 1 99 harm_ev | 98,945 14.6762 10.37709 1 99 man_coll | 98,945 1.613169 1.77203 0 9 -------------+--------------------------------------------------------- sch_bus | 98,945 .0059225 .0767298 0 1 veh_no | 98,945 1.303906 .7392198 0 14 make | 91,644 27.35088 21.84946 1 99 body_typ | 91,644 17.88883 22.09678 1 99 mod_year | 91,644 86.61632 6.082976 23 99 -------------+--------------------------------------------------------- rollover | 91,644 .3279538 .6847862 0 2 tow_veh | 91,644 .0888765 .6225602 0 9 spec_use | 91,644 .0527149 .616282 0 9 emer_use | 91,644 .002226 .0471283 0 1 impact1 | 91,644 10.32413 13.14417 0 99 -------------+--------------------------------------------------------- impact2 | 91,644 10.69653 14.1446 0 99 impacts | 91,644 1.187988 .6596498 0 9 fire_exp | 91,644 .0273013 .1629608 0 1 wgtcd_tr | 29,117 3.396332 3.157899 1 9 per_no | 98,945 1.754429 1.734975 1 46 -------------+--------------------------------------------------------- n_mot_no | 98,945 .0802365 .753187 0 99 age | 98,945 35.9405 22.07116 0 99 sex | 98,945 1.453889 1.040797 1 9 per_typ | 98,945 1.688342 1.128473 1 9 seat_pos | 98,945 14.38366 13.13661 0 99 -------------+--------------------------------------------------------- location | 98,945 .8379908 3.629685 0 99 ejection | 98,945 .192703 .7703729 0 9 extricat | 98,945 .1802415 1.012233 0 9 alc_det | 98,945 8.167689 2.263828 1 9 drinking | 98,945 4.414685 3.97127 0 9 -------------+--------------------------------------------------------- inj_sev | 98,945 2.57918 1.650964 0 9 hospital | 98,945 .8383445 1.569518 0 9 death_mo | 98,945 2.838243 4.406253 0 99 death_da | 98,945 6.510759 9.848138 0 99 death_yr | 98,945 38.68263 46.26 0 99 -------------+--------------------------------------------------------- death_hr | 98,945 7.338552 16.57123 0 99 death_mn | 98,945 13.10358 22.25937 0 99 lag_hrs | 98,945 625.4847 477.1426 0 999 lag_mins | 98,945 68.20341 40.87902 0 99 p_cf1 | 98,945 .5365607 5.043362 0 99 -------------+--------------------------------------------------------- p_cf2 | 98,945 .369195 4.736827 0 99 p_cf3 | 98,945 .2478751 4.245375 0 99 work_inj | 98,945 5.019728 3.897671 0 9 st_case | 98,945 269353.8 161226.3 10001 560135 mak_mod | 91,644 27629.69 21986.11 1001 99999 -------------+--------------------------------------------------------- vin_wgt | 64,215 3612.488 2403.958 101 9999 whlbs_sh | 87,124 1684.505 2230.431 109 9999 whlbs_lg | 87,124 966.6241 2498.288 0 9999 mcycl_ds | 6,110 6425.39 4479.448 49 9999 death_tm | 98,945 746.9588 1674.404 0 9999 -------------+--------------------------------------------------------- cert_no | 0 ser_tr | 0 vina_mod | 0 vin_bt | 0 rest_use | 98,945 10.84758 28.376 0 99 -------------+--------------------------------------------------------- air_bag | 98,945 8.176775 2.495774 0 9 ej_path | 98,945 .9702966 2.718875 0 9 alc_res | 98,945 66.55278 42.53364 0 99 drugs | 98,945 6.879984 2.852487 0 9 drug_det | 98,945 7.887523 .8611055 1 8 -------------+--------------------------------------------------------- drugtst1 | 98,945 1.604194 3.193056 0 9 drugres1 | 98,945 171.898 370.7181 0 999 drugtst2 | 98,945 .7407954 2.441487 0 9 drugres2 | 98,945 84.10761 273.9531 0 999 drugtst3 | 98,945 .718005 2.426311 0 9 -------------+--------------------------------------------------------- drugres3 | 98,945 80.53141 270.9622 0 999 by Jean Roth , jroth@nber.org , 18 Apr 2016