Summary statistics for person dataset : by Jean Roth , jroth@nber.org , 18 Apr 2016 Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- state | 100,716 27.40551 16.20541 1 56 veh_no | 100,716 1.354353 .892118 0 32 per_no | 100,716 1.730341 1.624513 1 41 n_mot_no | 100,716 .0659478 .4028885 0 99 age | 100,716 36.80348 21.85533 0 99 -------------+--------------------------------------------------------- sex | 100,716 1.437785 .9801139 1 9 per_typ | 100,716 1.637227 1.070741 1 19 seat_pos | 100,716 14.53901 13.19394 0 99 rest_use | 100,716 10.28661 27.45119 0 99 air_bag | 100,716 25.04409 16.78197 0 99 -------------+--------------------------------------------------------- ejection | 100,716 .1902478 .7509888 0 9 ej_path | 100,716 .952093 2.688682 0 9 extricat | 100,716 .1576611 .768332 0 9 location | 100,716 .6957087 3.24774 0 99 drinking | 100,716 4.567507 3.987958 0 9 -------------+--------------------------------------------------------- alc_det | 100,716 8.055135 2.308206 1 9 atst_typ | 100,716 1.05442 2.302827 0 9 alc_res | 100,716 66.58055 42.78153 0 99 drugs | 100,716 6.506871 3.183757 0 9 drug_det | 100,716 7.749156 1.20963 1 8 -------------+--------------------------------------------------------- drugtst1 | 100,716 1.535317 3.076624 0 9 drugres1 | 100,716 182.1275 375.9431 0 999 drugtst2 | 100,716 .6003713 2.189023 0 9 drugres2 | 100,716 71.10358 251.2014 0 999 drugtst3 | 100,716 .5719945 2.167239 0 9 -------------+--------------------------------------------------------- drugres3 | 100,716 65.48874 245.4008 0 999 inj_sev | 100,716 2.569026 1.651163 0 9 hospital | 100,716 2.215944 2.7964 0 9 death_mo | 100,716 2.989227 6.046233 0 99 death_da | 100,716 6.750377 10.76078 0 99 -------------+--------------------------------------------------------- death_hr | 100,716 7.080523 15.6492 0 99 death_mn | 100,716 13.34669 22.20683 0 99 lag_hrs | 100,716 446.7439 491.0881 0 999 lag_mins | 100,716 50.70294 44.88514 0 99 race | 100,716 8.951517 27.53819 0 99 -------------+--------------------------------------------------------- hispanic | 100,716 12.00602 29.26998 0 99 p_cf1 | 100,716 .4420648 4.634044 0 99 p_cf2 | 100,716 .3793935 4.605773 0 99 p_cf3 | 100,716 .2225069 4.002342 0 99 work_inj | 100,716 5.316911 3.850916 0 9 -------------+--------------------------------------------------------- st_case | 100,716 274814.5 161963.3 10001 560132 death_yr | 100,716 839.0526 1017.476 0 9999 death_tm | 100,716 721.399 1581.552 0 9999 cert_no | 0 make | 94,325 28.19126 22.71478 1 99 -------------+--------------------------------------------------------- body_typ | 94,325 19.39185 22.18913 1 99 rollover | 94,325 .3462815 .6961245 0 2 tow_veh | 94,325 .0857567 .5751792 0 9 spec_use | 94,325 .0453962 .569979 0 9 emer_use | 94,325 .0020037 .0654958 0 9 -------------+--------------------------------------------------------- impact1 | 94,325 10.46849 13.32082 0 99 impact2 | 94,325 10.75018 14.03241 0 99 impacts | 94,325 1.218616 .7196564 0 9 fire_exp | 94,325 .0282428 .1656666 0 1 mak_mod | 94,325 28480.95 22847.14 1001 99999 -------------+--------------------------------------------------------- mod_year | 94,325 2079.988 832.9391 0 9999 vina_mod | 0 ser_tr | 0 vin_bt | 0 whlbs_sh | 90,837 1882.761 2502.214 109 9999 -------------+--------------------------------------------------------- whlbs_lg | 90,837 1126.111 2796.871 0 9999 mcycl_ds | 7,382 6094.195 4488.216 49 9999 vin_wgt | 65,716 3809.245 2418.552 82 9999 wgtcd_tr | 32,069 3.563005 3.16487 1 9 county | 100,716 90.33592 95.46019 0 840 -------------+--------------------------------------------------------- month | 100,716 6.686415 3.352292 1 12 day | 100,716 15.63184 8.89577 1 99 hour | 100,716 13.32864 8.81332 0 99 minute | 100,716 28.45405 18.07076 0 99 ve_forms | 100,716 1.837067 1.236604 1 32 -------------+--------------------------------------------------------- road_fnc | 100,716 9.749742 14.62739 1 99 harm_ev | 100,716 14.96305 10.67526 1 99 man_coll | 100,716 1.65359 1.791708 0 9 sch_bus | 100,716 .0073176 .0852299 0 1 by Jean Roth , jroth@nber.org , 18 Apr 2016