Minitab系統(tǒng)的基本操作(英文版)(-)課件

INTRODUCTIONTOMINITABVERSION13WorksheetConventionsandMenuStructuresMinitabInteroperabilityGraphicCapabilitiesPareto HistogramBoxPlotScatterPlotStatisticalCapabilitiesCapabilityAnalysisHypothesisTestContingencyTablesANOVADesignofExperiments(DOE)MinitabTrainingAgendaWorksheetFormatandStructureSessionWindowWorksheetDataWindowMenuBarToolBarTextColumnC1-T(Designatedby-T)NumericColumnC3(NoAdditionalDesignation)DataWindowColumnConventionsDateColumnC2-D(Designatedby-D)ColumnNames(Type,Date,Count&AmountEnteredDataforDataRows1through4DataEntryArrowDataRowsOtherDataWindowConventionsMenuBar-MenuConventionsHotKeyAvailable(Ctrl-S)SubmenuAvailable(…attheendofselection)MenuBar-FileMenuKeyFunctionsWorksheetFileManagementSavePrintDataImportMenuBar-EditMenuKeyFunctionsWorksheetFileEditsSelectDeleteCopyPasteDynamicLinksMenuBar-ManipMenuKeyFunctionsDataManipulationSubset/SplitSortRankRowDataManipulationColumnDataManipulationMenuBar-CalcMenuKeyFunctionsCalculationCapabilitiesColumnCalculationsColumn/RowStatisticsDataStandardizationDataExtractionDataGenerationMenuBar-StatMenuKeyFunctionsAdvancedStatisticalToolsandGraphsHypothesisTestsRegressionDesignofExperimentsControlChartsReliabilityTestingMenuBar-GraphMenuKeyFunctionsDataPlottingCapabilitiesScatterPlotTrendPlotBoxPlotContour/3DplottingDotPlotsProbabilityPlotsStem&LeafPlotsMenuBar-DataWindowEditorMenuKeyFunctionsAdvancedEditandDisplayOptionsDataBrushingColumnSettingsColumnInsertion/MovesCellInsertionWorksheetSettingsNote:TheEditorSelectionisContextSensitive.Menuselectionswillvaryfor:DataWindowGraphSessionWindowDependingonwhichisselected.MenuBar-SessionWindowEditorMenuKeyFunctionsAdvancedEditandDisplayOptionsFontConnectivitySettingsMenuBar-GraphWindowEditorMenuKeyFunctionsAdvancedEditandDisplayOptionsBrushingGraphManipulationColorsOrientationFontMenuBar-WindowMenuKeyFunctionsAdvancedWindowDisplayOptionsWindowManagement/DisplayToolbarManipulation/DisplayMenuBar-HelpMenuKeyFunctionsHelpandTutorialsSubjectSearchesStatguideMultipleTutorialsMinitabontheWebMINITABINTEROPERABILITYMinitabInteroperabilityExcelMinitabPowerPointStartingwithExcel...Loadfile“Sample1”inExcel….StartingwithExcel...ThedataisnowloadedintoExcel….StartingwithExcel...HighlightandCopytheData….MovetoMinitab...OpenMinitabandselectthecolumnyouwanttopastethedatainto….MovetoMinitab...SelectPastefromthemenuandthedatawillbeinsertedintotheMinitabWorksheet….UseMinitabtodotheAnalysis...LetssaythatwewouldliketotestcorrelationbetweenthePredictedWorkloadandtheactualworkload….SelectStat…Regression….FittedLinePlot…..UseMinitabtodotheAnalysis...Minitabisnowaskingforustoidentifythecolumnswiththeappropriatedate….Clickintheboxfor“Response(Y):Notethatouroptionsnowappearinthisbox.Select“ActualWorkload”andhittheselectbutton…..Thiswillenterthe“ActualWorkload”dataintheResponse(Y)datafield...UseMinitabtodotheAnalysis...NowclickinthePredictor(X):box….Thenclickon“PredictedWorkload”andhittheselectbutton…Thiswillfillinthe“Predictor(X):”datafield...Bothdatafieldsshouldnowbefilled….SelectOK...UseMinitabtodotheAnalysis...Minitabnowdoestheanalysisandpresentstheresults...NotethatinthiscasethereisagraphandananalysissummaryintheSessionWindow…Let’ssaywewanttousebothinourPowerPointpresentation….TransferringtheAnalysis...Let’stakecareofthegraphfirst….GotoEdit….CopyGraph...TransferringtheAnalysis...OpenPowerPointandselectablankslide….GotoEdit….PasteSpecial...TransferringtheAnalysis...Select“Picture(EnhancedMetafile)…Thiswillgiveyouthebestgraphicswiththeleastamountoftrouble.TransferringtheAnalysis...OurMinitabgraphisnowpastedintothepowerpointpresentation….Wecannowsizeandpositionitaccordingly….TransferringtheAnalysis...NowwecancopytheanalysisfromtheSessionwindow…..Highlightthetextyouwanttocopy….SelectEdit…..Copy…..TransferringtheAnalysis...Nowgobacktoyourpowerpointpresentation…..SelectEdit…..Paste…..TransferringtheAnalysis...Wellwegotourdata,butitisabitlarge…..Reducethefontto12andweshouldbeok…..Presentingtheresults....Nowallweneedtodoistunethepresentation…..Herewepositionthegraphandsummaryandputintheappropriatetakeaway...Thenwearereadytopresent….GraphicCapabilitiesParetoChart....Let’sgenerateaParetoChartfromasetofdata….GotoFile…OpenProject….LoadthefilePareto.mpj….Nowlet’sgeneratetheParetoChart...ParetoChart....Goto:Stat…QualityTools…ParetoChart….ParetoChart....Filloutthescreenasfollows:OurdataisalreadysummarizedsowewillusetheChartDefectstable...Labelsin“Category”…Frequenciesin“Quantity”….AddtitleandhitOK..ParetoChart....MinitabnowcompletesourparetoforusreadytobecopiedandpastedintoyourPowerPointpresentation….Histogram....Let’sgenerateaHistogramfromasetofdata….GotoFile…OpenProject….Loadthefile2_Correlation.mpj….Nowlet’sgeneratetheHistogramoftheGPAresults...Histogram....Goto:Graph…Histogram…Histogram....Filloutthescreenasfollows:SelectGPAforourXvalueGraphVariableHitOK…..Histogram....MinitabnowcompletesourhistogramforusreadytobecopiedandpastedintoyourPowerPointpresentation….Thisdatadoesnotlooklikeitisverynormal….Let’suseMinitabtotestthisdistributionfornormality…...Histogram....Goto:Stat…BasicStatistics…DisplayDescriptiveStatistics….Histogram....Filloutthescreenasfollows:SelectGPAforourVariable….SelectGraphs…..Histogram....SelectGraphicalSummary….SelectOK…..SelectOKagainonthenextscreen...Histogram....NotethatnowwenotonlyhaveourHistogrambutanumberofotherdescriptivestatisticsaswell….Thisisagreatsummaryslide...Asforthenormalityquestion,notethatourPvalueof.038rejectsthenullhypothesis(P<.05).So,weconcludewith95%confidencethatthedataisnotnormal…..Histogram....Let’slookatanother“Histogram”toolwecanusetoevaluateandpresentdata….GotoFile…OpenProject….Loadthefileoverfill.mpj….Histogram....Goto:Graph…MarginalPlot…Histogram....Filloutthescreenasfollows:Selectfiller1fortheYVariable….SelectheadfortheXVariableSelectOK…..Histogram....NotethatnowwenotonlyhaveourHistogrambutadotplotofeachheaddataaswell...Notethatheadnumber6seemstobethesourceofthehighreadings…..ThistypeofHistogramiscalleda“MarginalPlot”..Boxplot....Let’slookatthesamedatausingaBoxplot….Boxplot....Goto:Stat…BasicStatistics…DisplayDescriptiveStatistics...Boxplot....Filloutthescreenasfollows:Select“filler1”forourVariable….SelectGraphs…..Boxplot....SelectBoxplotofdata….SelectOK…..SelectOKagainonthenextscreen...Boxplot....WenowhaveourBoxplotofthedata...Boxplot....ThereisanotherwaywecanuseBoxplotstoviewthedata...Goto:Graph…Boxplot...Boxplot....Filloutthescreenasfollows:Select“filler1”forourYVariable….Select“head”forourXVariable….SelectOK…..Boxplot....Notethatnowwenowhaveaboxplotbrokenoutbyeachofthevariousheads..Notethatheadnumber6againseemstobethesourceofthehighreadings…..Scatterplot....Let’slookatdatausingaScatterplot….GotoFile…OpenProject….Loadthefile2_Correlation.mpj….Nowlet’sgeneratetheScatterplotoftheGPAresultsagainstourMathandVerbalscores...Scatterplot....Goto:Graph…Plot...ScatterPlot....Filloutthescreenasfollows:SelectGPAforourYVariable….SelectMathandVerbalforourXVariables…..SelectOKwhendone...Scatterplot....WenowhavetwoScatterplotsofthedatastackedontopofeachother…Wecandisplaythisbetterbytilingthegraphs….Scatterplot....Todothis:GotoWindow…Tile...Scatterplot....NowwecanseebothScatterplotsofthedata…Scatterplot....Thereisanotherwaywecangeneratethesescatterplots….Goto:Graph…MatrixPlot...ScatterPlot....Filloutthescreenasfollows:Clickinthe“Graphvariables”blockHighlightallthreeavailabledatasets…Clickonthe“Select”button...SelectOKwhendone...Scatterplot....WenowhaveaseriesofScatterplots,eachonecorrespondingtoacombinationofthedatasetsavailable…NotethatthereappearstobeastrongcorrelationbetweenVerbalandbothMathandGPAdata….MinitabStatisticalToolsPROCESSCAPABILITYANALYSISLet’sdoaprocesscapabilitystudy….OpenMinitabandloadthefileCapability.mpj….SETTINGUPTHETEST….GotoStat…QualityTools….CapabilityAnalysis(Weibull)….Select“Torque”foroursingledatacolumn...Enteralowerspecof10andanupperspecof30.Thenselect“OK”….SETTINGUPTHETEST….Notethatthedatadoesnotfitthenormalcurveverywell...NotethattheLongTermcapability(Ppk)is0.43.ThisequatestoaZvalueof3*0.43=1.29standarddeviationsorsigmavalues.ThisequatestoanexpecteddefectratePPMof147,055.INTERPRETINGTHEDATA….HYPOTHESISTESTINGLoadthefilenormality.mpj…..SettingupthetestinMinitabCheckingtheDataforNormality….It’simportantthatwecheckfornormalityofdatasamples.Let’sseehowthisworks….GotoSTAT….BasicStatistics...NormalityTest….SetuptheTestWewilltestthe“Before”columnofdata….CheckAnderson-DarlingClickOKAnalyzingtheResultsSincethePvalueisgreaterthan.05wecanassumethe“Before”dataisnormalNowrepeatthetestforthe“After”Data(thisislefttothestudentasalearningexercise..)Checkingforequalvariance..Wenowwanttoseeifwehaveequalvariancesinoursamples.Toperformthistest,ourdatamustbe“stacked”.ToaccomplishthisgotoManip…Stack…StackColumns….Selectbothoftheavailablecolumns(BeforeandAfter)tostack....Typeinthelocationwhereyouwantthestackeddata….InthisexamplewewilluseC4….Typeinthelocationwhereyouwantthesubscriptsstored…InthisexamplewewilluseC3….SelectOK….Checkingforequalvariance..Nowthatwehaveourdatastacked,wearereadytotestforequalvariances.…GotoStat…ANOVA….TestforequalVariances...Checkingforequalvariance..Settingupthetest….Ourresponsewillbetheactualreceiptperformanceforthetwoweekswearecomparing.InthiscasewehadputthestackeddataincolumnC4….Ourfactorsisthelabelcolumnwecreatedwhenwestackedthedata(C3)..WesetourConfidenceLevelforthetest(95%).Thenselect“OK”.Here,weseethe95%confidenceintervalsforthetwopopulations.Sincetheyoverlap,weknowthatwewillfailtorejectthenullhypothesis.TheFtestresultsareshownhere.WecanseefromtheP-Valueof.263thatagainwewouldfailtorejectthenullhypothesis.NotethattheFtestassumesnormalityNotethatwegetagraphicalsummaryofbothsetsofdataaswellastherelevantstatistics….Analyzingthedata….Levene’stestalsocomparesthevarianceofthetwosamplesandisrobusttononnormaldata.Again,theP-Valueof.229indicatesthatwewouldfailtorejectthenullhypothesis.Herewehaveboxplotrepresentationsofbothpopulations.Letstestthedatawitha2SampletTest--UnderStat…BasicStatistics….Weseeseveralofthehypothesistestswhichwediscussedinclass.Inthisexamplewewillbeusinga2SampletTest….GotoStat….BasicStatistics..2Samplet…..Sincewealreadyhaveourdatastacked,wewillloadC4foroursamplesandC3foroursubscripts.Settingupthetest….Sincewehavealreadytestedforequalvariances,wecancheckoffthisbox…NowselectGraphs….Settingupthetest….Weseethatwehavetwooptionsforourgraphicaloutput.Forthissmallasample,Boxplotswillnotbeofmuchvaluesoweselect“Dotplotsofdata”andhit“OK”.HitOKagainonthenextscreen….Inthesessionwindowwehaveeachpopulation’sstatisticscalculatedforus..NotethatherewehaveaPvalueof.922.Wethereforefindthatthedatadoesnotsupporttheconclusionthatthereisasignificantdifferencebetweenthemeansofthetwopopulations...Interpretingtheresults….Thedotplotshowshowclosethedatapointsinthetwopopulationsfalltoeachother.Theclosevaluesofthetwopopulationmeans(indicatedbytheredbar)alsoshowslittlechancethatthishypothesiscouldberejectedbyalargersampleInterpretingtheresults….PairedComparisonsInpairedcomparisonswearetryingto“pair”observationsortreatments.Anexamplewouldbetotestautomaticbloodpressurecuffsandanursemeasuringthebloodpressureonthesamepatientusingamanualinstrument.Itcanalsobeusedinmeasurementsystemstudiestodetermineifoperatorsaregettingthesamemeanvalueacrossthesamesetofsamples.Let’slookatanexample:2_Hypothesis_Testing_Shoe_wear.mpj2_Hypothesis_Testing_Shoe_wear.mpj

Inthisexamplewearetryingtodetermineifshoematerial“A”wearrateisdifferentfromshoematerial“B”.Ourdatahasbeencollectedusingtenboys,whomwereaskedtowearoneshoemadefromeachmaterial.Ho:Material“A”wearrate=Material“B”wearrateHa:Material“A”wearrateMaterial“B”wearratePairedComparisonGotoStat….BasicStatistics…Pairedt…..PairedComparisonSelectthesamples…GotoGraphs….PairedComparisonSelecttheBoxplotforourgraphicaloutput..ThenselectOK..PairedComparisonWeseehowthe95%confidenceintervalofthemeanrelatestothevaluewearetesting.Inthiscase,thevaluefallsoutsidethe95%confidenceintervalofthedatamean.Thisgivesusconfirmationthattheshoematerialsaresignificantlydifferent.CONTINGENCYTABLES

(CHISQUARE)Enteringthedata….Enterthedatainatableformat.Forthisexample,loadthefileContingencyTable.mpj...Let’ssetupacontingencytable….ContingencytablesarefoundunderStat….Tables…ChiSquareTest….Selectthecolumnswhichcontainthetable.Thenselect“OK”Settingupthetest….Notethatyouwillhavethecriticalpopulationandteststatisticsdisplayedinthesessionwindow.Minitabbuildsthetableforyou.Notethatouroriginaldataispresentedanddirectlybelow,Minitabcalculatestheexpectedvalues.Here,MinitabcalculatestheChiSquarestatisticforeachdatapointandtotalstheresult.ThecalculatedChiSquarestatisticforthisproblemis30.846.PerformingtheAnalysis….ANalysisOfVArianceANOVALet’ssetuptheanalysisLoadthefileAnovaexample.mpj…StackthedatainC4andplacethesubscriptsinC5Setuptheanalysis….SelectStat…ANOVA…Oneway…SelectC4ResponsesC5FactorsThenselectGraphs….Setuptheanalysis….Chooseboxplotsofdata...ThenOKSetuptheanalysis….NotethatthePvalueislessthan.05thatmeansthatwerejectthenullhypothesisAnalyzingtheresults….Let’sLookAtMainEffects….ChooseStatANOVAMainEffectsPlot….MainEffectsSelectC4ResponseC5FactorsOKAnalyzingMainEffects..Formulation1HasLowestFuelConsumptionDESIGNOFEXPERIMENTS(DOE)

FUNDAMENTALSFirstCreateanExperimentalDesign...GotoStat…DOE…Factorial...CreateFactorialDesign...FirstCreateanExperimentalDesign...Select2LevelFactorialdesignwith3factorsThengotoDisplayAvailableDesigns….BowlingExample(continued)Wecannowseetheavailableexperimentaldesigns….WewillbeusingtheFull(Factorial)for3factorsandwecanseethatitwillrequire8runs…Now,selectOKandgobacktothemainscreen.OnceatthemainscreenselectDesigns...BowlingExample(continued)Selectyourdesign….WewillbeusingtheFull(Factorial)andagainwecanseethatitwillrequire8runs…Now,selectOKandgobacktothemainscreen.OnceatthemainscreenselectFactors...BowlingExample(continued)Fillinthenamesforyourfactors….Thenfillintheactualconditionsforlow(-)orhigh(+)Now,selectOKandgobacktothemainscreen.OnceatthemainscreenselectOptions...BowlingExample(continued)RemovetheoptiontoRandomizeRuns….Now,selectOKandgobacktothemainscreen.OnceatthemainscreenselectOK...BowlingExample(continued)Minitabhasnowdesignedourexperimentforus….Now,typeyourDatafromeachofyourexperimentaltreatmentsintoC8.Wearenowreadytoanalyzetheresults…BowlingExample(continued)GotoStat….DOE…Factorial...AnalyzeFactorialDesign...BowlingExample(continued)HighlightyourDatacolumnanduseSelecttoplaceitintheResponsesbox.Then,selecttheTermsOption.BowlingExample(continued)NotethatSelectedTermshasalloftheavailablechoicesalreadyselected.Weneeddonothingfurther.SelectOK.Then,atthemainscreenselectGraphsBowlingExample(continued)SelectyourEffectsPlotsandresetyourAlphato.05.SelectOKtoreturntothemainscreenandthenselectOKagain.BowlingExample(continued)Notethatonlyoneeffecthasasignificancegreaterthan95%.Alltheremainingfactorsandinteractionsarenotstatisticallysignificant.BowlingExample(continued)AnotherwaywecanlookatthedataistolookattheFactorialPlotsoftheresultingdata.GotoDOE….Factorial…FactorialPlots….BowlingExample(continued)SelectMainEffectsPlotandthenSetup…BowlingExample(continued)SelectC8asyourresponseSelect“Wristband”,“Ball”and“Lane”asyourfactors.Thenselect“OK”andOKagainonthemainscreen.BowlingExample(continued)Themagnitudeoftheverticaldisplacementindicatesthestrengthofthemaineffectforthatfactor.Hereweseethatthewristbandhasdramaticallymoreeffectthananyotherfactor.Weknowfromourearlierplotsthatthewristbandistheonlystatisticallysignificanteffect@95%confidence.Thisplotalsoshowsyouthedirectionofthemaineffects.Weclearlyseethatthe“with”conditionisrelatedtothehigherlevelofperformance.BowlingExample(continued)Nowletslookattheinteractions....GotoDOE….Factorial…FactorialPlots…BowlingExample(continued)SelectInteractionPlotandthenSetup…..BowlingExample(continued)SelectC8asyourresponsevariable.Select“Wristband”,“Ball”and“Lane”asyourfactors.Thenselect“OK”andOKagainonthenextscreen….BowlingExample(continued)Themorethelinesdivergefrombeingparallel,themoretheinteraction.Weseethatthestrongestinteraction(stillnotsignificant)isbetweenthelaneandtheball.Weknowfromourearlieranalysisthatnoneoftheseinteractionswerestatisticallysignificantforthisexperiment…..BowlingExample(SessionWindow)YoucanalsoseethatthereiszeroerrorThisisbecauseonly1runwasperformedwithnoreplicationsThisiswhereMinitabshowsustheMainEffectsandInteractionEffects..NotethatWristbandhasthestrongesteffectfollowedbytheinteractionbetweentheWristbandandtheLane...（第14講）考場(chǎng)作文開拓文路能力?分解層次(網(wǎng)友來稿)江蘇省鎮(zhèn)江中學(xué)陳乃香說明：本系列稿共24講，20XX年1月6日開始在資源上連載【要義解說】文章主旨確立以后，就應(yīng)該恰當(dāng)?shù)胤纸鈱哟?，使幾個(gè)層次構(gòu)成一個(gè)有機(jī)的整體，形成一篇完整的文章。如何分解層次主要取決于表現(xiàn)主旨的需要?！静呗越庾x】一般說來，記人敘事的文章常按時(shí)間順序分解層次，寫景狀物的文章常按時(shí)間順序、空間順序分解層次；說明文根據(jù)說明對(duì)象的特點(diǎn)，可按時(shí)間順序、空間順序或邏輯順序分解層次；議論文主要根據(jù)“提出問題－—分析問題——解決問題”順序來分解層次。當(dāng)然，分解層次不是一層不變的固定模式，而應(yīng)該富于變化。文章的層次，也常常有些外在的形式：1．小標(biāo)題式。即圍繞話題把一篇文章劃分為幾個(gè)相對(duì)獨(dú)立的部分，再給它們加上一個(gè)簡(jiǎn)潔、恰當(dāng)?shù)男?biāo)題。如《世界改變了模樣》四個(gè)小標(biāo)題：壽命變“長(zhǎng)”了、世界變“小”了、勞動(dòng)變“輕”了、文明變“綠”了。2．序號(hào)式。序號(hào)式作文與小標(biāo)題作文有相同的特點(diǎn)。序號(hào)可以是“一、二、三”