Summary statistics for person dataset : by Jean Roth , jroth@nber.org , 22 Apr 2016 Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- state | 1,100 43 0 43 43 county | 1,100 72 0 72 72 month | 1,100 6.799091 3.551339 1 12 day | 1,100 16.23818 9.122441 1 31 hour | 1,100 14.21455 6.92698 0 24 -------------+--------------------------------------------------------- minute | 1,100 23.71182 16.91793 0 58 ve_forms | 1,100 1.469091 .7035262 0 3 road_fnc | 1,100 4.723636 2.168512 2 8 harm_ev | 1,100 13.20091 6.655749 1 33 man_coll | 1,100 1.105455 1.688091 0 9 -------------+--------------------------------------------------------- sch_bus | 1,100 .0045455 .0672972 0 1 veh_no | 1,100 1.041818 .7087625 0 3 make | 871 26.01378 19.03052 1 99 body_typ | 871 13.32606 19.96892 2 99 mod_year | 871 74.28703 4.530135 48 99 -------------+--------------------------------------------------------- rollover | 871 .2146958 .6034878 0 2 tow_veh | 871 .0022962 .0478913 0 1 spec_use | 871 .0034443 .1016511 0 3 emer_use | 871 0 0 0 0 impact1 | 871 8.493685 6.311795 0 99 -------------+--------------------------------------------------------- impact2 | 871 8.421355 6.241902 0 99 impacts | 871 .9609644 .3045116 0 3 fire_exp | 871 .0149254 .121324 0 1 wgtcd_tr | 808 8.517327 1.807926 1 9 per_no | 1,100 1.58 1.094265 1 8 -------------+--------------------------------------------------------- age | 1,100 33.29091 17.62528 0 99 sex | 1,100 1.201818 .5129766 1 9 per_typ | 1,100 1.727273 .858603 1 8 seat_pos | 1,100 20.71273 39.19505 0 99 man_rest | 1,100 .2990909 1.158346 0 9 -------------+--------------------------------------------------------- aut_rest | 1,100 .0081818 .2713602 0 9 location | 1,100 2.112727 7.42558 0 99 ejection | 1,100 .0136364 .1160287 0 1 extricat | 1,100 .0072727 .0850083 0 1 drinking | 1,100 .1654545 .3717593 0 1 -------------+--------------------------------------------------------- test_res | 1,100 72.04818 39.18439 0 97 inj_sev | 1,100 2.680909 1.536632 0 9 hospital | 1,100 .7136364 .5792872 0 9 death_mo | 1,100 3.118182 4.151437 0 12 death_da | 1,100 7.227273 9.988036 0 31 -------------+--------------------------------------------------------- death_yr | 1,100 37.04 40.37121 0 82 death_hr | 0 death_mn | 0 lag_hrs | 0 lag_mins | 0 -------------+--------------------------------------------------------- p_cf1 | 1,100 1.269091 7.534232 0 99 p_cf2 | 1,100 .5509091 7.29716 0 99 p_cf3 | 1,100 .54 7.294983 0 99 st_case | 1,100 430232.1 133.332 430001 430462 mak_mod | 871 2656.316 1904.405 101 9900 -------------+--------------------------------------------------------- vin_wgt | 813 8154.653 3269.869 1610 9999 whlbs_sh | 813 7715.413 3922.609 866 9999 whlbs_lg | 813 7493.568 4306.637 0 9999 mcycl_ds | 621 9783.565 1420.649 75 9999 death_tm | 0 -------------+--------------------------------------------------------- vina_mod | 0 ser_tr | 0 by Jean Roth , jroth@nber.org , 22 Apr 2016