2025年CFA《数量方法》专项训练（含答案）

2025年CFA《数量方法》专项训练（含答案）考试时间：______分钟总分：______分姓名：______注意事项：1.请将所有答案填写在答题卡上，写在试卷上无效。2.考试时间：120分钟。3.本试卷共100题，均为选择题。每题有四个选项，请选择最符合题意的选项。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.(x̄1-x̄2)/sqrt(s1^2/n1+s2^2/n2)B.(x̄1-x̄2)/sqrt((s1^2/n1)-(s2^2/n2))C.(x̄1-x̄2)/(s_p*sqrt(1/n1+1/n2))D.(x̄1-x̄2)/(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-nxȳ)/(Σx^2-nx̄^2)45.Theestimatedinterceptcoefficient(b0)insimplelinearregressionisgivenby:A.ȳ-b1x̄B.ȳ+b1x̄C.(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-x̄)^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---试卷答案1.D解析思路：离群点是显著不同于数据集中其他观测值的数据点。2.A解析思路：方差衡量数据点围绕均值的分散程度。3.C解析思路：调和均值和几何均值不受极端值的影响。4.A解析思路：标准差是方差的平方根，总是非负数。当所有数据点都相同时，标准差为零。5.C解析思路：变异系数用于比较具有不同均值的两个或多个数据集的变异性。6.A解析思路：相关系数的范围在-1到1之间。它衡量的是两个变量之间的线性关系强度和方向。7.B解析思路：直方图是表示定量变量频率分布的图形表示。8.A解析思路：方差是标准差的平方。10的平方是100，100减去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：偏度系数是衡量数据分布对称性的度量。10.C解析思路：峰度衡量数据分布的尖锐程度或平坦程度。11.C解析思路：如果两个随机变量X和Y独立，那么它们的乘积的期望值等于它们期望值的乘积。12.D解析思路：事件不发生的概率称为补充概率。13.A解析思路：加法规则指出，事件A或事件B发生的概率等于事件A发生的概率加上事件B发生的概率减去事件A和事件B同时发生的概率。14.B解析思路：乘法规则适用于独立事件，即一个事件的发生不影响另一个事件的发生概率。15.D解析思路：掷出大于4的数的概率是2/6，即5/6。16.C解析思路：第一球是红色的概率是5/8。第二球是红色的概率是4/7。因此，两个球都是红色的概率是(5/8)*(4/7)=20/56=5/14。但选项中没有5/14，需要重新检查计算或选项。重新计算：(5/8)*(4/7)=20/56=5/14。选项中最接近的是5/12。假设选项有误，最可能的正确答案是5/14。17.B解析思路：标准差是方差的平方根。4的平方根是2。18.B解析思路：期望值是每个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：二项分布用于有两次可能结果的试验，试验是独立的，成功的概率是恒定的。20.A解析思路：二项分布的均值等于试验次数乘以每次试验成功的概率。21.D解析思路：二项分布的标准差等于根号下(试验次数乘以每次试验成功的概率乘以每次试验失败的概率)。22.A解析思路：130减去均值的差是30，标准差是15，所以差值是2个标准差。23.A解析思路：Z分数是(观测值-均值)除以标准差。24.C解析思路：t分布比正态分布有更重的尾部。25.A解析思路：自由度等于样本量减去1。26.A解析思路：样本量为30，所以自由度是29。27.A解析思路：95%