Probability, AUC, and Excel Linest Function.txt

Keep the 125 outcomes in the Histogram Spreadsheet unchanged. Change the bin ranges so that bin 1 is [-3, -1), bin 2 is [-1,1) bin 3 is [1, 3). Histograms Spreadsheet.xsx !hat is the approximate probabiit" that a ne# outcome #i $a #ithin bin 1% 5& .'

x x

(se the xce *robabiit" +unctions Spreadsheet. xce*robabiit"+unctions.xsx ssume a continuous uni$orm probabiit" distribution oer the range ['/, 51.50. !hat is the se#ness o$ the probabiit" distribution% 

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(se the xce *robabiit" +unctions Spreadsheet, proided in uestion 42. ssume a continuous uni$orm probabiit" distribution oer the range [-12, 20 !hat is the entrop" o$ this distribution%  bits 3 bits

x x

(se the xce *robabiit" +unctions Spreadsheet that #as preious" proided. ssume a 6aussian *robabiit" $unction #ith mean 7 3 and standard deiation 7'. !hat is the aue o$ $8x) at $83.5)% '.5 .352

x x

(se the xce *robabiit" +unctions Spreadsheet preious" proided in this ui9. ssume a 6aussian *robabiit" :istribution #ith mean 7 3 and standard deiation 7 '. !hat is the cumuatie distribution at x 7 /% .; .<'1

x r

(se the (C Cacuator Spreadsheet. (CCacuator and =eie# o$ (C Cure.xsx >$ the the �modi$ication modi$ication $actor� in the the origina origina exampe gien in the the (C Cacuator Cacuator Spreadsheet is changed $rom -1 to -2, #hat is the change in the actua rea (nder

the =?C Cure% @he area increases Ao change r

x

(se the (C Cacuator Spreadsheet proided in uestion 4. >$ the �modi$ication $actor� in the origina exampe gien in the (C Cacuator Spreadsheet is changed $rom -1 to -2, #hat is the threshod 8ro# 1) that resuts in the o#est cost per eent% 1.3 .'5

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=e$er to the (C Cacuator Spreadsheet preious" proided. ssume a binar" cassi$ication mode is trained on 2 ordered pairs o$ scores and outcomes and has an (C o$ .;1 on this � training set.� @he same mode, on 5, ne# scores and outcomes, has an (C o$ .5. !hich statement is most ie" to be correct% @he origina mode identi$ied signa as noise and has no predictie aue on ne# data. r

=e$er to the xce Binest +unction Spreadsheet. xce Binest +unction.xsx >$ a mutiariate inear regression gies a #eight beta81) o$ .' on x81) 7 � age in "ears,� and a ne# input x8/) o$ � age in months� is added to the regression data, #hich o$ the $oo#ing statements is $ase% (sing xce inest, and incuding x81) and x8/) data, the ne# beta8/) on the age in months #i be . x >$ the x81) data are remoed, the ne# beta8/) on the ne# x8/) data #i be .'. r

(se the xce Binest +unction Spreadsheet that #as proided in uestion 4;. !hat is the Correation, = $or the inear regression sho#n in the exampe% .//< or - .//<

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