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 -2  (nbme21#40)
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uosQient ,ssay ttah a yudts si oedn ot rsueame aeru eitnngro in mne agde 56. hWat of het lowonlfig rwnssea voediprd sha CEAATIRUNC dna CPREIES seermsau

I do aereg tath rof a hglyih siecper esremuaemnt yuo need a bgi orpug so oryu ndatdsar errro fo hte mnea si elrow e(i. seniacrgni hte tyuds .orwep)


eAg si yerall ntroipmta he,re escni leopep agde 65 RAE LAYULSU ESEDHUCDL ot eht tgisloruo , ecnhe a CITNENRAAU rauseem lwduo be oeelpp ton mfro aeagvre aeg 65 g&t-; emn gigon to a laclo ppnoishg cr.tnee sTih guorp sdeo not etfcerl eth ravegea NBU taht yuo wluod nfid in a 65 eyar old aeml rupo,g os the

AENSRW :SI 005 NEM ROFM A TSIL FO NTIASPET DONUGGNRIE A NEOIRTU TLAHEH GCRSNEEIN TA A CLALO PGPNHISO NECERT tg-;& TRCAENNUIA DNA SEREIPC &;-gt eosD ont cletref rtuyl het UNB aemn fo 56 aery odl msael utb it oeds it sreeclipy ti(hw low tarsdnad rrroe of ,neam ssel iaenotdvi fo lss)uter

I ophe mi rihgt, fi mi nto lapsee enixpla me hw.y (: !!

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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