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Welcome to ellomon’s page.
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 -2  (nbme21#40)
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tQiensuo ssay, tath a dystu si dneo to urmeesa areu teirongn ni enm dgea 6.5 tWha of teh liofolgnw wnasers iopdevrd sha ACNRITACEU nda CISEPER sueesrma

I do aerge ahtt rof a gyhlih cirepse nrtsemaumee oyu edne a gib uorpg os ryou ratndsda rroer of eht mane is lwoer (i.e gicrisenan het yduts )wroep.


eAg is eylarl natrmptio e,rhe ncsei eleppo daeg 56 RAE SYUULAL DDSULHCEE to eht golotisur , eecnh a NCEAURINTA asmeure udlow eb plpeeo ton from agareve ega 65 g;-&t men giong ot a olalc npopihgs cr.eent sihT gorpu edso not elctfer the earegav NBU tath uoy wlduo ifnd in a 65 arye ldo aelm upgro, os eht

ARWESN S:I 005 ENM FRMO A TILS OF TETPIANS REINGUGODN A IUNTROE EATHHL ENCRESIGN AT A LCOAL ONPPSIGH ECTENR -g&;t UNENAIACRT DNA RPEISCE &-tg; sDoe tno rfletec uylrt hte BNU enma of 56 eyar ldo mslea utb ti dseo ti cpreilesy whit( wlo nastaddr eorrr of ae,mn lses aviedntoi fo luss)rte

I pohe mi igrt,h fi mi not saepel ianepxl em yw.h (: !!

drdoom  Accuracy means the data points are dispersed, but when you take the mean of those points, that mean (“sample mean”) is nearby the population mean (“true mean”). Data points are “more precise” if the dispersion across data points is smaller than some other set of data points (notice how this is a comparison and not an “absolute” statement); precision says nothing about how close the average of the data points are to the “true mean.” +
drdoom  Keep in mind that “accuracy” and “precision” are relative descriptors; you can’t say “so-and-so is precise”; no, you can only say “such-and-such is more precise than so-and-so” or “so-and-so is more accurate than such-and-such.” So, in this case, we can infer that NBME considers “men at the urologist” to have BUNs that are closer to each other (more clustered; more precise; less dispersed) than the BUNs of “men at mall.” Here’s a nice image: +

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