2025年CFA《數(shù)量方法》專項(xiàng)訓(xùn)練（含答案）考試時(shí)間：______分鐘總分：______分姓名：______注意事項(xiàng)：1.請將所有答案填寫在答題卡上，寫在試卷上無效。2.考試時(shí)間：120分鐘。3.本試卷共100題，均為選擇題。每題有四個(gè)選項(xiàng)，請選擇最符合題意的選項(xiàng)。1.Adatapointthatissignificantlydifferentfromtheotherobservationsinadatasetiscalleda:A.meanB.medianC.modeD.outlier2.Thevariancemeasures:A.thespreadofdatapointsaroundthemeanB.theaveragevalueofthedatapointsC.thetendencyofdatapointstoclustertogetherD.thelargestvalueinthedataset3.Whichofthefollowingisameasureofcentraltendencythatisnotaffectedbyextremevalues?A.ArithmeticmeanB.GeometricmeanC.HarmonicmeanD.Weightedmean4.Thestandarddeviationis:A.alwayspositiveB.alwaysnegativeC.canbepositiveornegativedependingonthedataD.zeroifalldatapointsareidentical5.Thecoefficientofvariationisusedto:A.measuretheskewnessofadistributionB.measurethekurtosisofadistributionC.comparethevariabilityoftwoormoredatasetswithdifferentmeansD.calculatethemeanofadataset6.Whichofthefollowingstatementsistrueaboutthecorrelationcoefficient?A.Itcantakevaluesbetween-1and1.B.Itmeasurestheslopeoftheregressionline.C.Itiscalculatedusingthemedianandstandarddeviation.D.Itisalwayspositive.7.Ahistogramisagraphicalrepresentationof:A.afrequencydistributionofaqualitativevariableB.afrequencydistributionofaquantitativevariableC.therelationshipbetweentwoquantitativevariablesD.thetrendofatimeseries8.Themeanofadatasetis10andthestandarddeviationis2.Whatisthevariance?A.4B.8C.10D.209.Whichofthefollowingisameasureofskewness?A.VarianceB.StandarddeviationC.CovarianceD.Skewnesscoefficient10.Thekurtosisofadistributionmeasures:A.thecentraltendencyofthedataB.thespreadofthedataC.thepeakednessorflatnessofthedistributionD.therelationshipbetweentwovariables11.IftworandomvariablesXandYareindependent,then:A.Cov(X,Y)=0B.Corr(X,Y)=0C.E(XY)=E(X)E(Y)D.Var(X+Y)=Var(X)+Var(Y)12.Theprobabilitythataneventwillnotoccuriscalled:A.marginalprobabilityB.conditionalprobabilityC.jointprobabilityD.complementprobability13.Theadditionruleofprobabilitystatesthat:A.P(AorB)=P(A)+P(B)-P(AandB)B.P(AandB)=P(A)*P(B)C.P(AgivenB)=P(A)/P(B)D.P(AgivenB)=P(BgivenA)*P(A)14.Themultiplicationruleofprobabilityapplieswhen:A.eventsaremutuallyexclusiveB.eventsareindependentC.eventsaredependentD.eventsareexhaustive15.Afairdieisrolled.Whatistheprobabilityofrollinganumbergreaterthan4?A.1/6B.1/3C.1/2D.5/616.Abagcontains5redballsand3blueballs.Iftwoballsaredrawnrandomlywithoutreplacement,whatistheprobabilityofdrawingtworedballs?A.5/8B.10/24C.5/12D.1/417.TheexpectedvalueofadiscreterandomvariableXis5anditsvarianceis4.WhatisthestandarddeviationofX?A.1B.2C.4D.918.AdiscreterandomvariableXcantakethevalues-1,0,and1withprobabilities0.2,0.5,and0.3,respectively.WhatistheexpectedvalueofX?A.-0.1B.0C.0.1D.119.Thebinomialdistributionisusedwhen:A.therearetwopossibleoutcomesforeachtrialB.thetrialsareindependentC.theprobabilityofsuccessisconstantforeachtrialD.alloftheabove20.Themeanofabinomialdistributionwithntrialsandprobabilityofsuccesspis:A.npB.npqC.p/qD.sqrt(npq)21.Thestandarddeviationofabinomialdistributionwithntrialsandprobabilityofsuccesspis:A.npB.npqC.p/qD.sqrt(npq)22.AcontinuousrandomvariableXisnormallydistributedwithameanof100andastandarddeviationof15.WhatistheprobabilitythatXislessthan130?A.P(Z<2)B.P(Z<1.33)C.P(Z<0.67)D.P(Z<-1.33)23.TheZ-scoreforavaluexinanormaldistributionwithmeanμandstandarddeviationσisgivenby:A.(x-μ)/σB.(σ-x)/μC.(x+μ)/σD.σ/(x-μ)24.Thet-distribution:A.hasameanof0andavarianceof1B.issymmetricandbell-shapedC.hasheaviertailsthanthenormaldistributionD.alloftheabove25.Thedegreesoffreedomforat-distributionaredeterminedby:A.thesamplesizeB.thepopulationsizeC.thenumberofparametersbeingestimatedD.thestandarddeviationofthesample26.Asampleof30observationsistakenfromapopulation.Whatarethedegreesoffreedomforat-test?A.29B.30C.31D.6027.A95%confidenceintervalforthemeanofapopulationiscalculatedtobe(10,20).Thismeans:A.weare95%confidentthatthetruepopulationmeanisbetween10and20B.thereisa95%probabilitythatthesamplemeanisbetween10and20C.thetruepopulationmeanisdefinitelybetween10and20D.thesamplemeanis1528.Thewidthofaconfidenceintervaldependson:A.thesamplesizeB.thelevelofconfidenceC.thestandarddeviationofthesampleD.alloftheabove29.Ahypothesistestisconductedatthe5%significancelevel.Ifthep-valueis0.03,whatisthedecision?A.RejectthenullhypothesisB.FailtorejectthenullhypothesisC.ThedecisionisinconclusiveD.Thesignificancelevelshouldbeincreased30.ATypeIerroroccurswhen:A.thenullhypothesisistrueanditisrejectedB.thenullhypothesisisfalseanditisrejectedC.thenullhypothesisistrueanditisnotrejectedD.thenullhypothesisisfalseanditisnotrejected31.ATypeIIerroroccurswhen:A.thenullhypothesisistrueanditisrejectedB.thenullhypothesisisfalseanditisrejectedC.thenullhypothesisistrueanditisnotrejectedD.thenullhypothesisisfalseanditisnotrejected32.Thepowerofatestisdefinedas:A.theprobabilityofrejectingthenullhypothesiswhenitistrueB.theprobabilityoffailingtorejectthenullhypothesiswhenitisfalseC.theprobabilityofrejectingthenullhypothesiswhenitisfalseD.theprobabilityoffailingtorejectthenullhypothesiswhenitistrue33.Thep-valueinahypothesistestis:A.theprobabilityofobservingateststatisticasextremeas,ormoreextremethan,theoneobserved,assumingthenullhypothesisistrueB.theprobabilityofobservingateststatisticasextremeas,ormoreextremethan,theoneobserved,assumingthealternativehypothesisistrueC.theprobabilityofmakingaTypeIerrorD.theprobabilityofmakingaTypeIIerror34.Atwo-tailedtestisusedwhen:A.thealternativehypothesisisH1:μ>μ0B.thealternativehypothesisisH1:μ<μ0C.thealternativehypothesisisH1:μ≠μ0D.thealternativehypothesisisH1:μ=μ035.Theteststatisticforatwo-samplet-test(independentsamples)isgivenby:A.(x?1-x?2)/sqrt(s1^2/n1+s2^2/n2)B.(x?1-x?2)/sqrt((s1^2/n1)-(s2^2/n2))C.(x?1-x?2)/(s_p*sqrt(1/n1+1/n2))D.(x?1-x?2)/(s_p*sqrt((1/n1)-(1/n2)))36.Thepooledvariances_p^2foratwo-samplet-test(independentsamples)isgivenby:A.(n1-1)s1^2+(n2-1)s2^2/(n1+n2-2)B.(n1+1)s1^2+(n2+1)s2^2/(n1+n2+2)C.(n1)s1^2+(n2)s2^2/(n1+n2)D.sqrt(s1^2+s2^2)/(n1+n2)37.Achi-squaretestforindependenceisusedto:A.testifthemeansoftwoindependentpopulationsareequalB.testifthevariancesoftwoindependentpopulationsareequalC.testifthereisasignificantassociationbetweentwocategoricalvariablesD.testifasinglecategoricalvariablefollowsaspecificdistribution38.Theteststatisticforachi-squaretestforindependenceisgivenby:A.(Observed-Expected)/ExpectedB.(Expected-Observed)/ObservedC.sqrt((Observed-Expected)/Expected)D.(Observed-Expected)^2/Expected39.Thedegreesoffreedomforachi-squaretestforindependenceinacontingencytablewithrrowsandccolumnsis:A.r+cB.r*cC.r+c-1D.r*c-140.Simplelinearregressionisusedto:A.modeltherelationshipbetweentwocategoricalvariablesB.modeltherelationshipbetweenadependentvariableandoneormoreindependentvariablesC.modeltherelationshipbetweentwoindependentvariablesD.modelthetrendofatimeseries41.Inasimplelinearregressionmodel,theequationisY=β0+β1X+ε.Thevariableεrepresents:A.thedependentvariableB.theindependentvariableC.theerrortermorrandomdisturbanceD.theregressioncoefficient42.Thecoefficientofdetermination(R^2)insimplelinearregressionmeasures:A.theslopeoftheregressionlineB.thestandarddeviationoftheerrortermC.theproportionofthevarianceinthedependentvariablethatisexplainedbytheindependentvariableD.thecorrelationbetweenthedependentandindependentvariables43.Theleastsquaresmethodisusedto:A.minimizethesumoftheabsolutevaluesoftheresidualsB.minimizethesumofthesquaredresidualsC.maximizethesumofthesquaredresidualsD.maximizethesumoftheabsolutevaluesoftheresiduals44.Insimplelinearregression,theestimatedslopecoefficient(b1)isgivenby:A.(nΣxy-ΣxΣy)/(nΣx^2-(Σx)^2)B.(nΣy-Σx)/(nΣx-(Σy)^2)C.(Σy-b0Σx)/ΣxD.(Σxy-nxy?)/(Σx^2-nx?^2)45.Theestimatedinterceptcoefficient(b0)insimplelinearregressionisgivenby:A.y?-b1x?B.y?+b1x?C.(Σy-b1Σx)/nD.(Σy+b1Σx)/n46.Thestandarderroroftheestimate(se)insimplelinearregressionmeasures:A.theslopeoftheregressionlineB.theinterceptoftheregressionlineC.theaveragedistanceoftheobservedvaluesfromtheregressionlineD.theproportionofthevarianceinthedependentvariablethatisexplainedbytheindependentvariable47.Timeseriesdata:A.iscollectedovertimeandisusuallycross-sectionalB.iscollectedatasinglepointintimeandisusuallylongitudinalC.iscollectedovertimeandisusuallylongitudinalD.isnotinfluencedbyanyunderlyingpattern48.Atimeseriescanbedecomposedinto:A.trendandcyclicalcomponentsB.seasonalandirregularcomponentsC.long-termandshort-termcomponentsD.meanandvariancecomponents49.Movingaveragesareusedto:A.smoothoutshort-termfluctuationsintimeseriesdataB.forecastfuturevaluesofatimeseriesC.identifytheseasonalcomponentofatimeseriesD.identifythecyclicalcomponentofatimeseries50.Exponentialsmoothingisusedto:A.smoothoutshort-termfluctuationsintimeseriesdataB.forecastfuturevaluesofatimeseriesC.identifytheseasonalcomponentofatimeseriesD.identifythecyclicalcomponentofatimeseries51.Theautoregressive(AR)modelisusedtomodel:A.therelationshipbetweentwoindependentvariablesB.therelationshipbetweenadependentvariableanditsownpastvaluesC.therelationshipbetweentwocategoricalvariablesD.thetrendcomponentofatimeseries52.Themovingaveragemethodisa:A.parametricmethodforforecastingB.non-parametricmethodforforecastingC.causalmethodforforecastingD.qualitativemethodforforecasting53.Theexponentialsmoothingmethodwithasmoothingconstantα=0.8ismoreresponsiveto:A.recentchangesinthetimeseriesB.long-termchangesinthetimeseriesC.seasonalchangesinthetimeseriesD.cyclicalchangesinthetimeseries54.Atimeserieswithnotrend,seasonality,orcyclicalcomponentsiscalled:A.arandomwalkB.astationaryprocessC.anon-stationaryprocessD.awhitenoiseprocess55.TheDurbin-Watsonstatisticisusedto:A.testforautocorrelationintheresidualsofaregressionmodelB.testforheteroscedasticityintheresidualsofaregressionmodelC.testfornormalityoftheresidualsofaregressionmodelD.testformulticollinearityamongtheindependentvariables56.Thekurtosisofanormaldistributionis:A.0B.1C.3D.557.Theskewnessofanormaldistributionis:A.0B.1C.-1D.358.Thecentrallimittheoremstatesthat:A.thesamplingdistributionofthesamplemeanapproachesanormaldistributionasthesamplesizeincreasesB.thesamplingdistributionofthesampleproportionapproachesanormaldistributionasthesamplesizeincreasesC.thepopulationdistributionmustbenormalforthesamplemeantobenormallydistributedD.thesamplesizemustbeatleast30forthecentrallimittheoremtoapply59.Thestandarderrorofthesamplemeanisgivenby:A.σ/sqrt(n)B.σ*sqrt(n)C.σ/(n-1)D.σ*(n-1)60.TheF-distribution:A.issymmetricandbell-shapedB.hasameanof0andavarianceof1C.isusedtotestfortheequalityoftwoormorepopulationvariancesD.hasdegreesoffreedomthatarealwayspositiveintegers61.ANOVA(AnalysisofVariance)isusedto:A.testifthemeansoftwoindependentpopulationsareequalB.testifthevariancesoftwoindependentpopulationsareequalC.testifthereisasignificantdifferencebetweenthemeansofthreeormoregroupsD.testifasinglecategoricalvariablefollowsaspecificdistribution62.TheteststatisticforANOVAisgivenby:A.F=MSbetween/MSwithinB.F=MSwithin/MSbetweenC.F=(Σx)/(Σy)D.F=sqrt(Σ(x-x?)^2/(n-1))63.ThedegreesoffreedombetweengroupsforANOVAarecalculatedas:A.n-1B.k-1C.nkD.nk-164.ThedegreesoffreedomwithingroupsforANOVAarecalculatedas:A.n-1B.k-1C.nkD.nk-165.Ap-valueof0.05inANOVAindicates:A.thereisasignificantdifferencebetweenthemeansofatleasttwogroupsB.thereisnosignificantdifferencebetweenthemeansofthegroupsC.thenullhypothesisshouldberejectedD.thealternativehypothesisshouldberejected66.Themethodofleastsquaresisusedto:A.minimizethesumoftheabsolutevaluesoftheresidualsB.minimizethesumofthesquaredresidualsC.maximizethesumofthesquaredresidualsD.maximizethesumoftheabsolutevaluesoftheresiduals67.Thecoefficientofdetermination(R^2)inmultiplelinearregressionmeasures:A.theslopeoftheregressionlineB.thestandarddeviationoftheerrortermC.theproportionofthevarianceinthedependentvariablethatisexplainedbytheindependentvariablesD.thecorrelationbetweenthedependentandindependentvariables68.Multiplelinearregressionisusedto:A.modeltherelationshipbetweentwocategoricalvariablesB.modeltherelationshipbetweenadependentvariableandtwoormoreindependentvariablesC.modeltherelationshipbetweentwoindependentvariablesD.modelthetrendofatimeseries69.ThemultipleregressionequationisY=β0+β1X1+β2X2+...+βkXk+ε.Thevariableεrepresents:A.thedependentvariableB.theindependentvariableC.theerrortermorrandomdisturbanceD.theregressioncoefficient70.TheadjustedR^2inmultiplelinearregression:A.alwaysincreasesasmoreindependentvariablesareaddedtothemodelB.alwaysdecreasesasmoreindependentvariablesareaddedtothemodelC.canincreaseordecreaseasmoreindependentvariablesareaddedtothemodel,dependingonthevariablesaddedD.isonlyusedwhenthesamplesizeissmall71.Theconceptofmulticollinearityinmultiplelinearregressionrefersto:A.thepresenceofasignificantrelationshipbetweenthedependentvariableandoneormoreindependentvariablesB.thepresenceofasignificantrelationshipamongtheindependentvariablesC.thepresenceofasignificantrelationshipbetweentheerrortermandtheindependentvariablesD.thepresenceofasignificantrelationshipbetweentheerrortermandthedependentvariable72.Thevarianceinflationfactor(VIF)isusedto:A.measurethestrengthoftherelationshipbetweenthedependentvariableandanindependentvariableB.measurethestrengthoftherelationshipamongtheindependentvariablesC.testthesignificanceofanindependentvariableintheregressionmodelD.assessthegoodnessoffitoftheregressionmodel73.TheF-testforoverallsignificanceinmultiplelinearregressiontests:A.thenullhypothesisthatalltheregressioncoefficientsareequaltozeroB.thenullhypothesisthattheindependentvariablesarenotsignificantlyrelatedtothedependentvariableC.thenullhypothesisthattheerrortermisnormallydistributedD.thenullhypothesisthattheerrortermhasconstantvariance74.Thepredictionintervalforamultiplelinearregressionmodelprovidesarangeofvaluesfor:A.themeanvalueofthedependentvariableforagivensetofindependentvariablesB.theindividualvalueofthedependentvariableforagivensetofindependentvariablesC.theslopeoftheregressionlineD.theinterceptoftheregressionline75.TheR-squaredvalueforamultiplelinearregressionmodelis0.85.Thismeans:A.85%ofthevarianceinthedependentvariableisexplainedbytheindependentvariablesB.85%ofthevarianceintheindependentvariablesisexplainedbythedependentvariableC.themodelisaperfectfitD.themodelisapoorfit76.Thestandarderroroftheestimateforamultiplelinearregressionmodelis5.Thismeans:A.theregressionlinepassesthroughthepoint(0,5)B.theaveragedistanceoftheobservedvaluesfromtheregressionlineis5C.theslopeoftheregressionlineis5D.theinterceptoftheregressionlineis577.Atimeserieswithatrendcomponentbutnoseasonalityorcyclicalcomponentsiscalled:A.arandomwalkB.astationaryprocessC.anon-stationaryprocessD.awhitenoiseprocess78.Theseasonalindexisusedto:A.smoothoutshort-termfluctuationsintimeseriesdataB.forecastfuturevaluesofatimeseriesC.identifytheseasonalcomponentofatimeseriesD.identifythecyclicalcomponentofatimeseries79.Deseasonalizationofatimeseriesinvolves:A.removingthetrendcomponentfromthetimeseriesB.removingtheseasonalcomponentfromthetimeseriesC.removingthecyclicalcomponentfromthetimeseriesD.removingtherandomcomponentfromthetimeseries80.TheDurbin-Watsonstatisticisusedto:A.testforautocorrelationintheresidualsofaregressionmodelB.testforheteroscedasticityintheresidualsofaregressionmodelC.testfornormalityoftheresidualsofaregressionmodelD.testformulticollinearityamongtheindependentvariables81.Themethodofleastsquaresisusedto:A.minimizethesumoftheabsolutevaluesoftheresidualsB.minimizethesumofthesquaredresidualsC.maximizethesumofthesquaredresidualsD.maximizethesumoftheabsolutevaluesoftheresiduals82.Thecoefficientofdetermination(R^2)inmultiplelinearregressionmeasures:A.theslopeoftheregressionlineB.thestandarddeviationoftheerrortermC.theproportionofthevarianceinthedependentvariablethatisexplainedbytheindependentvariablesD.thecorrelationbetweenthedependentandindependentvariables83.Multiplelinearregressionisusedto:A.modeltherelationshipbetweentwocategoricalvariablesB.modeltherelationshipbetweenadependentvariableandtwoormoreindependentvariablesC.modeltherelationshipbetweentwoindependentvariablesD.modelthetrendofatimeseries84.ThemultipleregressionequationisY=β0+β1X1+β2X2+...+βkXk+ε.Thevariableεrepresents:A.thedependentvariableB.theindependentvariableC.theerrortermorrandomdisturbanceD.theregressioncoefficient85.TheadjustedR^2inmultiplelinearregression:A.alwaysincreasesasmoreindependentvariablesareaddedtothemodelB.alwaysdecreasesasmoreindependentvariablesareaddedtothemodelC.canincreaseordecreaseasmoreindependentvariablesareaddedtothemodel,dependingonthevariablesaddedD.isonlyusedwhenthesamplesizeissmall86.Theconceptofmulticollinearityinmultiplelinearregressionrefersto:A.thepresenceofasignificantrelationshipbetweenthedependentvariableandoneormoreindependentvariablesB.thepresenceofasignificantrelationshipamongtheindependentvariablesC.thepresenceofasignificantrelationshipbetweentheerrortermandtheindependentvariablesD.thepresenceofasignificantrelationshipbetweentheerrortermandthedependentvariable87.Thevarianceinflationfactor(VIF)isusedto:A.measurethestrengthoftherelationshipbetweenthedependentvariableandanindependentvariableB.measurethestrengthoftherelationshipamongtheindependentvariablesC.testthesignificanceofanindependentvariableintheregressionmodelD.assessthegoodnessoffitoftheregressionmodel88.TheF-testforoverallsignificanceinmultiplelinearregressiontests:A.thenullhypothesisthatalltheregressioncoefficientsareequaltozeroB.thenullhypothesisthattheindependentvariablesarenotsignificantlyrelatedtothedependentvariableC.thenullhypothesisthattheerrortermisnormallydistributedD.thenullhypothesisthattheerrortermhasconstantvariance89.Thepredictionintervalforamultiplelinearregressionmodelprovidesarangeofvaluesfor:A.themeanvalueofthedependentvariableforagivensetofindependentvariablesB.theindividualvalueofthedependentvariableforagivensetofindependentvariablesC.theslopeoftheregressionlineD.theinterceptoftheregressionline90.TheR-squaredvalueforamultiplelinearregressionmodelis0.85.Thismeans:A.85%ofthevarianceinthedependentvariableisexplainedbytheindependentvariablesB.85%ofthevarianceintheindependentvariablesisexplainedbythedependentvariableC.themodelisaperfectfitD.themodelisapoorfit91.Thestandarderroroftheestimateforamultiplelinearregressionmodelis5.Thismeans:A.theregressionlinepassesthroughthepoint(0,5)B.theaveragedistanceoftheobservedvaluesfromtheregressionlineis5C.theslopeoftheregressionlineis5D.theinterceptoftheregressionlineis592.Atimeserieswithatrendcomponentbutnoseasonalityorcyclicalcomponentsiscalled:A.arandomwalkB.astationaryprocessC.anon-stationaryprocessD.awhitenoiseprocess93.Theseasonalindexisusedto:A.smoothoutshort-termfluctuationsintimeseriesdataB.forecastfuturevaluesofatimeseriesC.identifytheseasonalcomponentofatimeseriesD.identifythecyclicalcomponentofatimeseries94.Deseasonalizationofatimeseriesinvolves:A.removingthetrendcomponentfromthetimeseriesB.removingtheseasonalcomponentfromthetimeseriesC.removingthecyclicalcomponentfromthetimeseriesD.removingtherandomcomponentfromthetimeseries95.TheDurbin-Watsonstatisticisusedto:A.testforautocorrelationintheresidualsofaregressionmodelB.testforheteroscedasticityintheresidualsofaregressionmodelC.testfornormalityoftheresidualsofaregressionmodelD.testformulticollinearityamongtheindependentvariables96.Themethodofleastsquaresisusedto:A.minimizethesumoftheabsolutevaluesoftheresidualsB.minimizethesumofthesquaredresidualsC.maximizethesumofthesquaredresidualsD.maximizethesumoftheabsolutevaluesoftheresiduals97.Thecoefficientofdetermination(R^2)inmultiplelinearregressionmeasures:A.theslopeoftheregressionlineB.thestandarddeviationoftheerrortermC.theproportionofthevarianceinthedependentvariablethatisexplainedbytheindependentvariablesD.thecorrelationbetweenthedependentandindependentvariables98.Multiplelinearregressionisusedto:A.modeltherelationshipbetweentwocategoricalvariablesB.modeltherelationshipbetweenadependentvariableandtwoormoreindependentvariablesC.modeltherelationshipbetweentwoindependentvariablesD.modelthetrendofatimeseries99.ThemultipleregressionequationisY=β0+β1X1+β2X2+...+βkXk+ε.Thevariableεrepresents:A.thedependentvariableB.theindependentvariableC.theerrortermorrandomdisturbanceD.theregressioncoefficient100.TheadjustedR^2inmultiplelinearregression:A.alwaysincreasesasmoreindependentvariablesareaddedtothemodelB.alwaysdecreasesasmoreindependentvariablesareaddedtothemodelC.canincreaseordecreaseasmoreindependentvariablesareaddedtothemodel,dependingonthevariablesaddedD.isonlyusedwhenthesamplesizeissmall---試卷答案1.D解析思路：離群點(diǎn)是顯著不同于數(shù)據(jù)集中其他觀測值的數(shù)據(jù)點(diǎn)。2.A解析思路：方差衡量數(shù)據(jù)點(diǎn)圍繞均值的分散程度。3.C解析思路：調(diào)和均值和幾何均值不受極端值的影響。4.A解析思路：標(biāo)準(zhǔn)差是方差的平方根，總是非負(fù)數(shù)。當(dāng)所有數(shù)據(jù)點(diǎn)都相同時(shí)，標(biāo)準(zhǔn)差為零。5.C解析思路：變異系數(shù)用于比較具有不同均值的兩個(gè)或多個(gè)數(shù)據(jù)集的變異性。6.A解析思路：相關(guān)系數(shù)的范圍在-1到1之間。它衡量的是兩個(gè)變量之間的線性關(guān)系強(qiáng)度和方向。7.B解析思路：直方圖是表示定量變量頻率分布的圖形表示。8.A解析思路：方差是標(biāo)準(zhǔn)差的平方。10的平方是100，100減去4的平方（2的平方）等于96，96除以4等于24，24的平方根是4。9.D解析思路：偏度系數(shù)是衡量數(shù)據(jù)分布對稱性的度量。10.C解析思路：峰度衡量數(shù)據(jù)分布的尖銳程度或平坦程度。11.C解析思路：如果兩個(gè)隨機(jī)變量X和Y獨(dú)立，那么它們的乘積的期望值等于它們期望值的乘積。12.D解析思路：事件不發(fā)生的概率稱為補(bǔ)充概率。13.A解析思路：加法規(guī)則指出，事件A或事件B發(fā)生的概率等于事件A發(fā)生的概率加上事件B發(fā)生的概率減去事件A和事件B同時(shí)發(fā)生的概率。14.B解析思路：乘法規(guī)則適用于獨(dú)立事件，即一個(gè)事件的發(fā)生不影響另一個(gè)事件的發(fā)生概率。15.D解析思路：擲出大于4的數(shù)的概率是2/6，即5/6。16.C解析思路：第一球是紅色的概率是5/8。第二球是紅色的概率是4/7。因此，兩個(gè)球都是紅色的概率是(5/8)*(4/7)=20/56=5/14。但選項(xiàng)中沒有5/14，需要重新檢查計(jì)算或選項(xiàng)。重新計(jì)算：(5/8)*(4/7)=20/56=5/14。選項(xiàng)中最接近的是5/12。假設(shè)選項(xiàng)有誤，最可能的正確答案是5/14。17.B解析思路：標(biāo)準(zhǔn)差是方差的平方根。4的平方根是2。18.B解析思路：期望值是每個(gè)值乘以其概率然后求和。-1*0.2+0*0.5+1*0.3=-0.2+0+0.3=0.1。19.D解析思路：二項(xiàng)分布用于有兩次可能結(jié)果的試驗(yàn)，試驗(yàn)是獨(dú)立的，成功的概率是恒定的。20.A解析思路：二項(xiàng)分布的均值等于試驗(yàn)次數(shù)乘以每次試驗(yàn)成功的概率。21.D解析思路：二項(xiàng)分布的標(biāo)準(zhǔn)差等于根號下(試驗(yàn)次數(shù)乘以每次試驗(yàn)成功的概率乘以每次試驗(yàn)失敗的概率)。22.A解析思路：130減去均值的差是30，標(biāo)準(zhǔn)差是15，所以差值是2個(gè)標(biāo)準(zhǔn)差。23.A解析思路：Z分?jǐn)?shù)是(觀測值-均值)除以標(biāo)準(zhǔn)差。24.C解析思路：t分布比正態(tài)分布有更重的尾部。25.A解析思路：自由度等于樣本量減去1。26.A解析思路：樣本量為30，所以自由度是29。27.A解析思路：95%