Summary statistics for person dataset : by Jean Roth , jroth@nber.org , 18 Apr 2016 Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- state | 102,120 27.83954 15.96232 1 56 county | 102,120 88.06274 94.94772 1 999 month | 102,120 6.756629 3.315115 1 12 day | 102,120 15.63969 8.866634 1 99 hour | 102,120 13.2193 8.853588 0 99 -------------+--------------------------------------------------------- minute | 102,120 29.9046 22.76729 0 99 ve_forms | 102,120 1.663455 .8495888 1 18 road_fnc | 102,120 4.414904 2.124469 1 9 harm_ev | 102,120 14.63213 10.25392 1 99 man_coll | 102,120 1.479553 1.745702 0 9 -------------+--------------------------------------------------------- sch_bus | 102,120 .0056306 .0748263 0 1 veh_no | 102,120 1.239023 .7255562 0 18 make | 92,867 27.25283 23.26104 1 99 body_typ | 92,867 19.89878 25.34012 1 99 mod_year | 92,867 76.03913 5.991381 1 99 -------------+--------------------------------------------------------- rollover | 92,866 .295921 .6569976 0 2 tow_veh | 92,867 .468821 1.883528 0 9 spec_use | 92,867 .4500307 1.937807 0 9 emer_use | 92,867 .0016798 .049521 0 9 impact1 | 92,867 9.688361 11.39046 0 99 -------------+--------------------------------------------------------- impact2 | 92,867 13.55335 21.2061 0 99 impacts | 92,867 1.124318 .671623 0 9 fire_exp | 92,867 .0278032 .1644095 0 1 wgtcd_tr | 35,822 5.374714 3.699041 0 9 per_no | 102,120 1.713337 1.838387 1 65 -------------+--------------------------------------------------------- n_mot_no | 102,120 .105611 1.194998 0 99 age | 102,120 33.52259 20.96442 0 99 sex | 102,120 1.405396 1.007381 1 9 per_typ | 102,120 1.738974 1.192677 1 9 seat_pos | 102,120 14.44016 14.92824 0 99 -------------+--------------------------------------------------------- man_rest | 102,120 1.940844 3.589833 0 9 aut_rest | 102,120 .4402174 1.94056 0 9 location | 102,120 1.114757 5.105204 0 99 ejection | 102,120 .2834508 1.199885 0 9 extricat | 102,120 .1707403 1.016607 0 9 -------------+--------------------------------------------------------- drinking | 102,120 3.820456 3.954288 0 9 test_res | 102,120 74.54084 37.90565 0 99 inj_sev | 102,120 2.628251 1.657146 0 9 hospital | 102,120 .8018214 1.249225 0 9 death_mo | 102,120 3.088122 5.771417 0 99 -------------+--------------------------------------------------------- death_da | 102,120 6.924295 10.52016 0 99 death_yr | 102,120 35.29607 40.61157 0 99 death_hr | 102,120 9.826812 22.3235 0 99 death_mn | 102,120 14.93421 25.72434 0 99 lag_hrs | 43,945 145.7979 331.7807 0 999 -------------+--------------------------------------------------------- lag_mins | 43,945 30.93779 34.76527 0 99 p_cf1 | 102,120 .5141108 4.755017 0 99 p_cf2 | 102,120 .2612123 4.27656 0 99 p_cf3 | 102,120 .1903839 4.076985 0 99 st_case | 102,120 279210.5 159518.5 10001 560174 -------------+--------------------------------------------------------- mak_mod | 92,867 2760.99 2341.029 101 9999 vin_wgt | 69,324 4762.848 3019.358 0 9999 whlbs_sh | 69,325 3196.191 3798.419 0 9999 whlbs_lg | 69,325 2535.172 4183.38 0 9999 mcycl_ds | 20,652 8941.436 2466.74 0 9999 -------------+--------------------------------------------------------- death_tm | 102,120 997.6154 2254.314 0 9999 vina_mod | 0 ser_tr | 0 vin_bt | 0 by Jean Roth , jroth@nber.org , 18 Apr 2016