Summary statistics for person dataset : by Jean Roth , jroth@nber.org , 18 Apr 2016 Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- state | 103,347 27.31242 16.15395 1 56 county | 103,347 89.85889 95.48408 0 999 month | 103,347 6.754023 3.379865 1 12 day | 103,347 15.8773 8.93518 1 99 hour | 103,347 13.56247 8.789235 0 99 -------------+--------------------------------------------------------- minute | 103,347 28.03551 18.02271 0 99 ve_forms | 103,347 1.840111 1.565051 1 47 road_fnc | 103,347 8.076122 7.200031 1 99 harm_ev | 103,347 14.84482 10.55137 1 99 man_coll | 103,347 1.653604 1.795752 0 9 -------------+--------------------------------------------------------- sch_bus | 103,347 .006125 .0780227 0 1 veh_no | 103,347 1.348118 1.064342 0 47 make | 96,165 27.43596 21.94723 1 99 body_typ | 96,165 18.04713 21.81653 1 99 mod_year | 96,165 88.64964 6.002097 0 99 -------------+--------------------------------------------------------- rollover | 96,165 .3335413 .6889215 0 2 tow_veh | 96,165 .0885665 .6170683 0 9 spec_use | 96,165 .0405033 .538185 0 9 emer_use | 96,165 .0017678 .0420082 0 1 impact1 | 96,165 10.58984 13.53157 0 99 -------------+--------------------------------------------------------- impact2 | 96,165 10.65249 13.79554 0 99 impacts | 96,165 1.205584 .6928269 0 9 fire_exp | 96,165 .0248843 .1557734 0 1 wgtcd_tr | 31,202 3.417826 3.135896 1 9 per_no | 103,347 1.767211 1.809165 1 60 -------------+--------------------------------------------------------- n_mot_no | 103,347 .072871 .5097715 0 99 age | 103,347 36.24774 22.14825 0 99 sex | 103,347 1.455785 1.031816 1 9 per_typ | 103,347 1.684751 1.375185 1 99 seat_pos | 103,347 14.49284 13.22512 0 99 -------------+--------------------------------------------------------- location | 103,347 .7559968 3.378047 0 99 ejection | 103,347 .1914231 .7798906 0 9 extricat | 103,347 .1595886 .9153016 0 9 alc_det | 103,347 8.181786 2.254281 1 9 drinking | 103,347 4.47178 3.975082 0 9 -------------+--------------------------------------------------------- inj_sev | 103,347 2.569634 1.661985 0 9 hospital | 103,347 .7148925 1.219191 0 9 death_mo | 103,347 2.805248 4.560568 0 99 death_da | 103,347 6.513445 9.963748 0 99 death_yr | 103,347 39.07637 47.16531 0 99 -------------+--------------------------------------------------------- death_hr | 103,347 6.909286 15.41193 0 99 death_mn | 103,347 12.6903 21.56402 0 99 lag_hrs | 103,347 625.7254 477.0925 0 999 lag_mins | 103,347 68.34333 40.72737 0 99 p_cf1 | 103,347 .541738 4.804718 0 99 -------------+--------------------------------------------------------- p_cf2 | 103,347 .3392068 4.309512 0 99 p_cf3 | 103,347 .1825984 3.626263 0 99 work_inj | 103,347 4.983473 3.897626 0 9 st_case | 103,347 273877.1 161444.8 10001 560121 mak_mod | 96,165 27721.12 22079.7 1001 99999 -------------+--------------------------------------------------------- vin_wgt | 67,802 3661.88 2401.258 108 9999 whlbs_sh | 92,635 1731.104 2298.888 90 9999 whlbs_lg | 92,635 993.989 2572.824 0 9999 mcycl_ds | 6,270 6557.012 4437.742 49 9999 death_tm | 103,347 703.6189 1557.564 0 9999 -------------+--------------------------------------------------------- cert_no | 0 ser_tr | 0 vina_mod | 0 vin_bt | 0 rest_use | 103,347 10.80894 28.36274 0 99 -------------+--------------------------------------------------------- air_bag | 103,347 7.973855 2.629981 0 9 ej_path | 103,347 .9442074 2.682497 0 9 alc_res | 103,347 67.38864 42.27178 0 99 drugs | 103,347 6.808596 2.916259 0 9 drug_det | 103,347 7.838989 1.02674 1 8 -------------+--------------------------------------------------------- drugtst1 | 103,347 1.655123 3.255271 0 9 drugres1 | 103,347 178.7656 376.3702 0 999 drugtst2 | 103,347 .7151635 2.401619 0 9 drugres2 | 103,347 81.27108 269.484 0 999 drugtst3 | 103,347 .6933631 2.387436 0 9 -------------+--------------------------------------------------------- drugres3 | 103,347 77.66626 266.4917 0 999 by Jean Roth , jroth@nber.org , 18 Apr 2016