Summary statistics for person dataset : by Jean Roth , jroth@nber.org , 18 Apr 2016 Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- state | 1,438 43 0 43 43 county | 1,438 72 0 72 72 month | 1,438 6.726704 3.479695 1 12 day | 1,438 15.9242 9.145873 1 31 hour | 1,438 13.62726 7.407054 0 24 -------------+--------------------------------------------------------- minute | 1,438 24.51739 16.48932 0 55 ve_forms | 1,438 1.547288 .7099474 1 4 road_fnc | 1,438 4.511822 1.976075 1 8 harm_ev | 1,438 14.51252 10.20122 1 43 man_coll | 1,438 .9248957 1.318961 0 9 -------------+--------------------------------------------------------- sch_bus | 1,438 0 0 0 0 veh_no | 1,438 1.077191 .7312642 0 4 make | 1,159 37.0811 22.52004 1 99 body_typ | 1,159 16.5289 27.26175 2 99 mod_year | 1,159 80.22261 6.942931 58 99 -------------+--------------------------------------------------------- rollover | 1,159 .1604832 .5091139 0 2 tow_veh | 1,159 .2355479 1.408307 0 9 spec_use | 1,159 .230371 1.413447 0 9 emer_use | 1,159 0 0 0 0 impact1 | 1,159 10.74029 16.06197 0 99 -------------+--------------------------------------------------------- impact2 | 1,159 10.84124 16.26366 0 99 impacts | 1,159 .9180328 .3208542 0 2 fire_exp | 1,159 .0224331 .1481514 0 1 wgtcd_tr | 554 7.442238 3.060172 1 9 per_no | 1,438 1.661335 1.259085 1 12 -------------+--------------------------------------------------------- n_mot_no | 1,438 .3198887 2.257108 0 52 age | 1,438 36.55633 22.41667 0 99 sex | 1,438 1.456189 1.455616 1 9 per_typ | 1,438 2.105702 1.587164 1 9 seat_pos | 1,438 26.27469 35.85365 0 99 -------------+--------------------------------------------------------- man_rest | 1,438 .3727399 1.52689 0 9 aut_rest | 1,438 .0438108 .6266189 0 9 location | 1,438 2.616829 7.111003 0 99 ejection | 1,438 .0139082 .1171508 0 1 extricat | 1,438 .0104312 .2458331 0 9 -------------+--------------------------------------------------------- drinking | 1,438 6.582058 2.953339 0 9 test_res | 1,438 64.55285 42.03996 0 99 inj_sev | 1,438 2.514604 1.471888 0 4 hospital | 1,438 .5340751 .4990111 0 1 death_mo | 1,438 2.790682 4.003999 0 12 -------------+--------------------------------------------------------- death_da | 1,438 6.310153 9.502945 0 31 death_yr | 1,438 35.40751 42.34198 0 87 death_hr | 1,438 5.840056 10.40158 0 99 death_mn | 1,438 10.09388 17.19232 0 99 lag_hrs | 592 47.45101 146.498 0 999 -------------+--------------------------------------------------------- lag_mins | 592 8.761824 17.75569 0 99 p_cf1 | 1,438 .6717663 3.963918 0 99 p_cf2 | 1,438 .150904 3.698281 0 99 p_cf3 | 1,438 .1425591 3.695224 0 99 st_case | 1,438 430287.6 170.6921 430001 430587 -------------+--------------------------------------------------------- mak_mod | 1,159 3755.997 2250.52 199 9999 vin_wgt | 1,020 6420.505 3820.984 0 9999 whlbs_sh | 1,020 5178.698 4502.812 799 9999 whlbs_lg | 1,020 4698.574 4955.303 0 9999 mcycl_ds | 457 9568.149 1966.009 50 9999 -------------+--------------------------------------------------------- death_tm | 1,438 594.0994 1051.425 0 9999 vina_mod | 0 ser_tr | 0 vin_bt | 0 by Jean Roth , jroth@nber.org , 18 Apr 2016