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ISYE 6414 - MIDTERM EXAM 3 QUESTIONS AND 100% CORRECT ANSWERS 2024 $5.99   Add to cart

Exam (elaborations)

ISYE 6414 - MIDTERM EXAM 3 QUESTIONS AND 100% CORRECT ANSWERS 2024

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  • ISYE 6414

ISYE 6414 - MIDTERM EXAM 3 QUESTIONS AND 100% CORRECT ANSWERS 2024

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  • September 7, 2024
  • 12
  • 2024/2025
  • Exam (elaborations)
  • Questions & answers
  • ISYE 6414
  • ISYE 6414
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ISYE 6414 - MIDTERM EXAM 3
QUESTIONS AND 100% CORRECT
ANSWERS 2024
RegressionLAnalysisL-
LANSWERLRegressionLanalysisLisLaLsimpleLwayLtoLinvestigateLtheLrelationshipLbetweenL2LorLmoreLvariablesLi

nLaLnon-deterministicLway.



Response/TargetLVariableL(Y)L-
LANSWERLThisLisLaLvariableLwe'reLinterestedLinLunderstanding,LmodelingLorLtestingL




ThisLisLaLrandomLvariable.LItLvariesLwithLchangesLinLtheLpredictor(s)



2.LPredicting/ExplanatoryL(independent)LVariables(XsL~LX1,LX2)L-
LANSWERLTheseLareLvariablesLweLthinkLmightLbeLusefulLinLpredictingLorLmodelingLtheLresponseLvariableL




ThisLisLaLfixedLvariable.LItLdoesLnotLchangeLwithLtheLresponse



SimpleLLinearLRegressionL-LANSWERLWeLhaveLaLstraightLlineLwhichLdoesn'tLfitLperfectlyLtoLtheLpoints



TheLobjectiveLisLtoLfitLaLnon-deterministicLlinearLmodelLbetweenLtheLpredictingLvariableLandLY.L



InLsimpleLlinearLregression,LweLhaveL3LparametersLtoLestimate.



MultipleLLinearLRegressionL-LANSWERLWeLcanLhaveLaLplaneLifLweLhaveLtwoLpredictions



PolynomialLRegressionL-LANSWERLWeLareLcapturingLaLnonlinearLrelationship



ObjectivesLofLLinearLRegressionL-
LANSWERL1.LPrediction:LWeLwantLtoLseeLhowLtheLresponseLvariableLbehavesLinLdifferentLsettingsL

, 2.LModeling:LWeLareLinterestedLinLmodelingLtheLrelationshipLbetweenLtheLresponseLvariableLandLtheLexpla
natory/predictingLvariables



3.LTesting:LWeLareLalsoLinterestedLinLtestingLtheLhypothesesLofLassociationLrelationships.



SimpleLLinearLRegressionLAssumptionsL-
LANSWERL•LLinearity/MeanLZeroLAssumption:LThisLmeansLthatLtheLexpectedLvalueLofLtheLerrorsLisLzero




•LConstantLVarianceLAssumption:LThisLmeansLthatLtheLvarianceLofLtheLerrorLtermLisLequalLtoLsigma_square
dLisLtheLsameLacrossLallLerrorLterms



•LIndependenceLAssumption:LThisLmeansLthatLtheLerrorLtermsLareLindependentLrandomLvariablesLi.e.Ldevi
ancesL(responseLvariablesLYs)LareLindependentlyLdrawnLfromLtheLdataLgeneratingLprocessL--
LitLcannotLbeLtrueLthatLtheLmodelLunder-

predictsLYLforLoneLparticularLcaseLtellsLyouLanythingLorLallLaboutLwhatLitLdoesLforLanyLotherLcase



•LNormalLAssumption:LTheLerrorsLareLassumedLtoLbeLnormallyLdistributed.



LinearityLAssumptionL-
LANSWERLALviolationLofLthisLassumptionLwillLleadLtoLdifficultiesLinLestimatingL0LandLmeansLthatLyourLmodelL

doesLnotLincludeLaLnecessaryLsystematicLcomponent



ConstantLVarianceLAssumptionL-
LANSWERLThisLmeansLthatLtheLmodelLcannotLbeLmoreLaccurateLinLsomeLpartsLandLlessLaccurateLinLotherLpar

tsLofLtheLmodel.LTheLvarianceLhasLtoLbeLconstant.



LALviolationLofLthisLassumptionLmeansLthatLtheLestimatesLareLnotLasLefficientLasLtheyLcouldLbeLinLestimatingL
theLtrueLparametersLandLbetterLestimatesLcanLbeLcalculatedLalsoLresultsLinLpoorlyLcalibratedLpredictionLinte
rvals



IndependenceLAssumptionL-LANSWERLItLcannotLbeLtrueLthatLtheLmodelLunder-
predictsLY.LOneLparticularLcaseLdoesn'tLtellLyouLanythingLorLallLaboutLwhatLitLdoesLforLanyLotherLcase

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