Summary statistics for person dataset : by Jean Roth , jroth@nber.org , 18 Apr 2016 Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- state | 1,391 43 0 43 43 county | 1,391 72 0 72 72 month | 1,391 6.630482 3.522596 1 12 day | 1,391 15.5018 8.888103 1 31 hour | 1,391 15.07836 8.119098 0 99 -------------+--------------------------------------------------------- minute | 1,391 23.86485 16.53556 0 99 ve_forms | 1,391 1.552121 .7236852 1 5 road_fnc | 1,391 4.492451 2.215977 2 8 harm_ev | 1,391 14.74047 10.2819 1 44 man_coll | 1,391 1.051761 1.504495 0 6 -------------+--------------------------------------------------------- sch_bus | 1,391 0 0 0 0 veh_no | 1,391 1.079799 .7346229 0 5 make | 1,120 33.14911 24.64305 1 99 body_typ | 1,120 16.97321 27.97658 2 99 mod_year | 1,120 77.57411 7.45471 57 99 -------------+--------------------------------------------------------- rollover | 1,120 .1857143 .5571627 0 2 tow_veh | 1,120 .4946429 2.027507 0 9 spec_use | 1,120 .5419643 2.073284 0 9 emer_use | 1,120 0 0 0 0 impact1 | 1,120 13.23304 19.38238 0 99 -------------+--------------------------------------------------------- impact2 | 1,120 13.34464 19.36944 0 99 impacts | 1,120 1.005357 .3408026 0 3 fire_exp | 1,120 .0071429 .0842507 0 1 wgtcd_tr | 650 8.233846 2.198352 1 9 per_no | 1,391 1.688713 1.230959 1 8 -------------+--------------------------------------------------------- n_mot_no | 1,391 .1948239 .3962075 0 1 age | 1,391 36.37096 22.97591 0 99 sex | 1,391 1.53918 1.645052 1 9 per_typ | 1,391 2.115025 1.560206 1 8 seat_pos | 1,391 30.14234 38.61732 0 99 -------------+--------------------------------------------------------- man_rest | 1,391 .5859094 1.914632 0 9 aut_rest | 1,391 .0517613 .6808127 0 9 location | 1,391 2.89504 9.194175 0 99 ejection | 1,391 .0129403 .1130578 0 1 extricat | 1,391 .007908 .0886064 0 1 -------------+--------------------------------------------------------- drinking | 1,391 6.714594 2.922709 0 9 test_res | 1,391 64.06902 42.40461 0 99 inj_sev | 1,391 2.331416 1.546455 0 4 hospital | 1,391 .5700935 .4952406 0 1 death_mo | 1,391 2.688713 4.001458 0 12 -------------+--------------------------------------------------------- death_da | 1,391 6.372394 9.694287 0 31 death_yr | 1,391 32.91157 41.01963 0 84 death_hr | 1,391 5.615385 8.982927 0 99 death_mn | 1,391 8.358016 15.33801 0 99 lag_hrs | 545 42.81835 131.6826 0 999 -------------+--------------------------------------------------------- lag_mins | 545 12.67523 17.6046 0 99 p_cf1 | 1,391 2.053918 12.37464 0 99 p_cf2 | 1,391 1.628325 12.36597 0 99 p_cf3 | 1,391 1.56578 12.35598 0 99 st_case | 1,391 430245.5 147.6019 430001 430508 -------------+--------------------------------------------------------- mak_mod | 1,120 3367.176 2461.665 107 9999 vin_wgt | 1,023 7017.791 3686.8 0 9999 whlbs_sh | 1,023 6083.735 4464.775 866 9999 whlbs_lg | 1,023 5720.183 4885.712 0 9999 mcycl_ds | 589 9710.846 1625.361 171 9999 -------------+--------------------------------------------------------- death_tm | 1,391 569.8965 907.35 0 9999 vina_mod | 0 ser_tr | 0 vin_bt | 0 by Jean Roth , jroth@nber.org , 18 Apr 2016