Summary statistics for person dataset : by Jean Roth , jroth@nber.org , 18 Apr 2016 Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- state | 1,437 43 0 43 43 county | 1,437 72 0 72 72 month | 1,437 6.68476 3.470348 1 12 day | 1,437 15.29576 8.879388 1 31 hour | 1,437 13.61935 9.156971 0 99 -------------+--------------------------------------------------------- minute | 1,437 22.16145 17.69056 0 99 ve_forms | 1,437 1.535839 .7262509 1 5 road_fnc | 1,437 4.401531 1.959428 3 8 harm_ev | 1,437 15.11969 10.97501 1 43 man_coll | 1,437 .8211552 1.183992 0 5 -------------+--------------------------------------------------------- sch_bus | 1,437 0 0 0 0 veh_no | 1,437 1.08977 .7300836 0 5 make | 1,181 35.07282 24.20113 1 99 body_typ | 1,181 18.80356 30.53748 2 99 mod_year | 1,181 78.9094 7.568518 56 99 -------------+--------------------------------------------------------- rollover | 1,181 .1795089 .5492245 0 2 tow_veh | 1,181 .3996613 1.830847 0 9 spec_use | 1,181 .3928874 1.835087 0 9 emer_use | 1,181 .0025402 .0503579 0 1 impact1 | 1,181 12.57155 17.9278 0 99 -------------+--------------------------------------------------------- impact2 | 1,181 12.55715 17.92875 0 99 impacts | 1,181 .9390347 .2693534 0 3 fire_exp | 1,181 .0143946 .1191612 0 1 wgtcd_tr | 564 8.067376 2.448561 0 9 per_no | 1,437 1.773138 1.500706 1 15 -------------+--------------------------------------------------------- n_mot_no | 1,437 .1781489 .3827713 0 1 age | 1,437 35.96729 23.13168 0 99 sex | 1,437 1.533751 1.608996 1 9 per_typ | 1,437 2.061239 1.499445 1 8 seat_pos | 1,437 30.52679 38.86653 0 99 -------------+--------------------------------------------------------- man_rest | 1,437 .4224078 1.697655 0 9 aut_rest | 1,437 0 0 0 0 location | 1,437 2.853166 9.68343 0 99 ejection | 1,437 .0160056 .1412042 0 2 extricat | 1,437 .0104384 .1016693 0 1 -------------+--------------------------------------------------------- drinking | 1,437 7.409186 1.989072 0 9 test_res | 1,437 61.52401 43.28913 0 99 inj_sev | 1,437 2.495477 1.492605 0 4 hospital | 1,437 .5233125 .4996301 0 1 death_mo | 1,437 2.848991 4.055004 0 12 -------------+--------------------------------------------------------- death_da | 1,437 6.397356 9.425566 0 31 death_yr | 1,437 35.4913 41.93342 0 86 death_hr | 1,437 5.333333 9.316672 0 99 death_mn | 1,437 8.977731 15.90771 0 99 lag_hrs | 600 36.48 130.4601 0 999 -------------+--------------------------------------------------------- lag_mins | 600 9.835 18.07463 0 99 p_cf1 | 1,437 1.75087 11.32241 0 99 p_cf2 | 1,437 1.316632 11.31257 0 99 p_cf3 | 1,437 1.308977 11.31213 0 99 st_case | 1,437 430296 179.4754 430001 430600 -------------+--------------------------------------------------------- mak_mod | 1,181 3557.637 2417.05 107 9999 vin_wgt | 1,092 6292.957 3772.153 1444 9999 whlbs_sh | 1,092 5139.716 4493.307 0 9999 whlbs_lg | 1,092 4710.75 4899.474 0 9999 mcycl_ds | 497 9787.789 1406.115 97 9999 -------------+--------------------------------------------------------- death_tm | 1,437 542.3111 940.5307 0 9999 vina_mod | 0 ser_tr | 0 vin_bt | 0 by Jean Roth , jroth@nber.org , 18 Apr 2016