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Exam (elaborations)

STATS 210 FINAL EXAM QUESTIONS WITH COMPLETE ANSWERS.

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STATS 210 FINAL EXAM QUESTIONS WITH COMPLETE ANSWERS.

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  • November 1, 2024
  • 14
  • 2024/2025
  • Exam (elaborations)
  • Questions & answers
  • WEMT
  • WEMT
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LucieLucky
STATS 210 FINAL EXAM QUESTIONS
WITH COMPLETE ANSWERS

Exhibit pp1, ppQuestion pp1: ppBased ppsolely ppon ppthe ppgraph, ppcould ppyou ppsay ppeating
ppbreakfast ppand ppstudent ppperformance pphave ppa ppcause ppand ppeffect pprelationship?
ppExplain. pp- ppAnswer ppNo. ppFrom ppthe ppgraph ppwe pponly ppknow ppthey ppare
ppassociated ppand ppassociation ppdoes ppnot ppimply ppcausation.


Exhibit pp2, ppQuestion pp1: ppReportedly, ppthe ppLegislature ppwas pptold ppthat ppthis
ppgraph ppshows ppthat ppglobal ppwarming ppis ppgood ppbecause ppit ppcauses ppa
ppdecrease ppin ppinfant ppmortality. ppIs ppthis ppan ppaccurate ppassessment? ppExplain. pp-
ppAnswer ppThat ppis ppreally ppnot ppa ppcorrect ppexplanation. ppThe ppgraph ppshows pponly
ppcorrelation, ppnot ppcausation. ppProbably ppit ppis pphow ppindustrialized ppthe ppnation ppis
ppthat ppaffects ppboth ppcarbon ppfootprint ppand ppinfant ppmortality. ppCertainly ppit ppis ppnot
ppsaying ppthat ppa pplarge ppcarbon ppfootprint ppis ppdirectly ppresponsible ppfor ppa
ppreduction ppin ppinfant ppmortality.


Exhibit pp1, ppQuestion pp2: ppDoes ppthe ppscatterplot ppshow ppa pppositive ppassociation
ppor ppa ppnegative ppassociation, ppand pphow ppdo ppyou ppknow? pp- ppAnswer
ppAssociation ppis ppnegative pp(because ppscatterplot ppis ppdownwards ppto ppthe ppright).


Exhibit pp1, ppQuestion pp3: ppIs ppthe ppassociation ppweak ppor ppstrong, ppand pphow ppdo
ppyou ppknow? pp- ppAnswer ppPretty ppstrong. ppPoints ppare pppretty pptightly pppacked
ppabout ppthe ppcurvy pptrend ppwe ppsee ppin ppthe ppplot.


Exhibit pp2, ppQuestion pp1: ppRedo ppthe ppscatterplot ppfrom ppExhibit pp1. ppSame pprules
ppas ppbefore: ppuse ppa ppcomputer pppackage ppand ppsubmit ppprofessional-level
ppresults. ppThis pptime, ppplot pplog10 pp(Child ppMortality) ppversus pplog10 pp(CO2
ppEmissions). ppHow ppdoes ppthis ppplot ppcompare ppto ppthe ppone ppyou ppdid ppin ppExhibit
pp1? pp- ppAnswer ppThis ppone ppis ppmuch ppmore ppin ppthe ppshape ppof ppa ppstraight ppline
ppthan ppthe pporiginal ppone ppfrom ppExhibit pp1.


Exhibit pp2, ppQuestion pp2: ppDoes ppthe ppnew ppscatterplot ppshow ppa pppositive
ppassociation ppor ppa ppnegative ppassociation, ppand pphow ppdo ppyou ppknow? pp-
ppAnswer ppAssociation ppis ppnegative pp(because ppscatterplot ppis ppdownwards ppto ppthe
ppright).


Exhibit pp1, ppQuestion pp1: ppWhat ppis ppthe ppvalue ppof ppr? pp- ppAnswer ppr pp= pp-0.44

, Exhibit pp1, ppQuestion pp3: ppDo ppyou ppthink ppthe ppcomputation ppof ppr ppis ppappropriate
ppfor ppthese ppdata? ppWhy ppor ppwhy ppnot? pp- ppAnswer ppProbably ppnot. ppThat ppplot
ppwas ppnot ppa ppstraight-line ppplot ppso ppr ppmight ppbe ppdeceptive pphere.


Exhibit pp2, ppQuestion pp1: ppWhat ppis ppthe ppvalue ppof ppr? pp- ppAnswer ppr=-0.80

Do ppyou ppthink ppthe ppcomputation ppof ppr ppis ppappropriate ppfor ppthese ppdata? ppWhy
ppor ppwhy ppnot? pp(You ppconstructed ppa ppscatterplot ppof ppthese ppdata ppin ppBeyond
ppthe ppNumbers pp1.27.) pp- ppAnswer ppMakes ppmuch ppmore ppsense ppfor ppthese ppdata
ppsince ppthe pptransformed ppplot pplooked ppmuch ppmore pplike ppa ppstraight
line.

A ppplot ppvery ppsimilar ppto ppthe ppone ppshown pphere ppwas ppallegedly pppresented ppto
ppthe ppKentucky ppHouse ppof ppRepresentatives ppas pppart ppof ppan ppoverall ppmessage
ppthat pprelated ppCO2 ppemissions ppto ppchild ppmortality. ppHow ppdid pptaking pplog ppbase
pp10 ppof ppeach ppvariable ppshown, ppand ppmaking ppa ppnew ppplot, ppmake ppusing pp"r"
ppmore ppreasonable ppfor ppmeasuring ppassociation? pp- ppAnswer ppThe pptransformed
ppscatterplot ppwent ppfrom ppshowing ppa ppcurved pptrend ppto ppshowing ppa ppstraight
ppline pptrend.


In ppExcel ppwhat ppis ppthe ppfunction ppfor ppfinding ppthe ppcorrelation ppcoefficient?
ppGoogle ppon ppthis ppif ppyou ppdon't ppknow. pp- ppAnswer pp=CORREL( pp)


We pplooked ppat ppa ppstudy ppthat ppshowed ppcollege ppstudents ppwho ppate ppbreakfast
pphad ppa pphigher ppsuccess pprate ppon ppGeneral ppBiology ppexams ppthan ppthose
ppstudents ppwho ppdid ppnot ppeat ppbreakfast. ppThe ppoperative ppgraph ppis pprepeated
ppbelow. ppWhat ppdoes ppthe ppgraph pptell ppyou? pp- ppAnswer ppEating ppbreakfast ppis
ppassociated ppwith ppbetter ppclass ppperformance.


We pplooked ppat ppa ppstudy ppthat ppshowed ppcollege ppstudents ppwho ppate ppbreakfast
pphad ppa pphigher ppsuccess pprate ppon ppGeneral ppBiology ppexams ppthan ppthose
ppstudents ppwho ppdid ppnot ppeat ppbreakfast. ppThe ppoperative ppgraph ppis pprepeated
ppbelow. ppThe ppstudy ppwas ppdone ppon pp1,259 ppcollege ppstudents, pp825 ppof ppwhom
ppself-identified ppas pphaving ppeaten ppbreakfast ppbefore pptaking ppthe ppexam. ppWhat
ppcan ppyou ppsay ppabout ppthe ppnumber ppof ppstudents ppwho ppgot ppD's ppand ppE's ppin
ppeach ppof ppthe pptwo ppgroups? pp- ppAnswer ppThe ppBreakfast ppgroup pphad ppmore
ppD's ppand ppE's


Suppose ppwe pphave ppdata pplike ppin ppProblem pp4 ppthat ppcan ppbe ppinto ppa ppso-called
pp2x2 pptable pplike ppyou ppsee ppbelow. ppThe ppletters ppU, ppV, ppW, ppX ppjust ppstand ppfor
ppthe ppcounts ppthat ppare ppin ppthose ppcells. ppWhat ppis ppthe ppprobability ppof ppgetting
ppa ppGrade ppof ppC ppor ppBetter ppif ppyou ppate ppbreakfast, ppdivided ppby ppthe
ppprobability ppof ppgetting ppa ppGrade ppBelow ppC ppif ppyou ppate ppbreakfast? pp- ppAnswer
ppU/V


The ppcorrelation ppcoefficient ppis ppalways: pp- ppAnswer ppBetween pp-1 ppand pp1

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