Summary statistics for person dataset : by Jean Roth , jroth@nber.org , 18 Apr 2016 Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- state | 103,348 27.31529 16.15303 1 56 county | 103,348 87.14109 95.05882 0 999 month | 103,348 6.828569 3.303597 1 12 day | 103,348 15.69273 8.872716 1 99 hour | 103,348 13.44445 9.113765 0 99 -------------+--------------------------------------------------------- minute | 103,348 30.29323 22.5805 0 99 ve_forms | 103,348 1.694363 .8956123 1 23 road_fnc | 103,348 4.424914 2.151824 1 9 harm_ev | 103,348 14.61222 10.33282 1 99 man_coll | 103,348 1.50927 1.741525 0 9 -------------+--------------------------------------------------------- sch_bus | 103,348 .0073248 .0852712 0 1 veh_no | 103,348 1.259986 .7538525 0 23 make | 94,317 27.55837 23.08461 1 99 body_typ | 94,317 20.35818 25.31921 1 99 mod_year | 94,317 77.5438 5.832883 0 99 -------------+--------------------------------------------------------- rollover | 94,317 .2967546 .6582715 0 2 tow_veh | 94,317 .4297423 1.79213 0 9 spec_use | 94,317 .4085478 1.849851 0 9 emer_use | 94,317 .001601 .0399805 0 1 impact1 | 94,317 9.404996 11.04905 0 99 -------------+--------------------------------------------------------- impact2 | 94,317 12.94576 20.48371 0 99 impacts | 94,317 1.112228 .6141581 0 9 fire_exp | 94,317 .027397 .163238 0 1 wgtcd_tr | 35,155 5.02543 3.666625 0 9 per_no | 103,348 1.734373 1.974912 1 47 -------------+--------------------------------------------------------- n_mot_no | 103,348 .0999632 1.062296 0 99 age | 103,348 34.21596 21.40313 0 99 sex | 103,348 1.439331 1.107009 1 9 per_typ | 103,348 1.722452 1.184217 1 9 seat_pos | 103,348 14.69151 15.54048 0 99 -------------+--------------------------------------------------------- man_rest | 103,348 2.079721 3.636768 0 9 aut_rest | 103,348 .2481132 1.473345 0 9 location | 103,348 1.106649 5.301069 0 99 ejection | 103,348 .2769768 1.174123 0 9 extricat | 103,348 .1374579 .8885208 0 9 -------------+--------------------------------------------------------- drinking | 103,348 4.178968 3.967591 0 9 test_res | 103,348 70.64719 40.11327 0 99 inj_sev | 103,348 2.60125 1.653396 0 9 hospital | 103,348 .7175078 1.150502 0 9 death_mo | 103,348 3.069261 5.441717 0 99 -------------+--------------------------------------------------------- death_da | 103,348 6.941934 10.79922 0 99 death_yr | 103,348 35.97285 41.56684 0 99 death_hr | 103,348 8.49702 19.265 0 99 death_mn | 103,348 13.88463 23.77123 0 99 lag_hrs | 44,257 110.8009 289.7218 0 999 -------------+--------------------------------------------------------- lag_mins | 44,257 27.6404 32.669 0 99 p_cf1 | 103,348 .4645663 4.363889 0 99 p_cf2 | 103,348 .2310737 3.830935 0 99 p_cf3 | 103,348 .1468727 3.573525 0 99 st_case | 103,348 274000.8 161358.8 10001 560140 -------------+--------------------------------------------------------- mak_mod | 94,317 2791.818 2323.661 101 9999 vin_wgt | 68,548 4506.529 2919.9 0 9999 whlbs_sh | 68,548 2865.778 3584.532 0 9999 whlbs_lg | 68,548 2156.624 3956.054 0 9999 mcycl_ds | 18,214 7747.905 3988.787 49 9999 -------------+--------------------------------------------------------- death_tm | 103,348 863.5866 1945.802 0 9999 vina_mod | 0 ser_tr | 0 vin_bt | 0 by Jean Roth , jroth@nber.org , 18 Apr 2016