Microsoft Word - Math 119 Lab 3.docx Math119Lab3:InferencesforNumerical Data Thislabusesthenc.csvdatasetavailableonBlackboard. Studentsshouldcreateasingleword...

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It will require stat crunch it has been done before by others on here on my previous stats assignments i will provide my stats crunch log in info


Microsoft Word - Math 119 Lab 3.docx Math119Lab3:InferencesforNumerical Data Thislabusesthenc.csvdatasetavailableonBlackboard.Studentsshouldcreateasingleword documentwhichcontainstheirworkforall12exercises.Besuretoincludeanytablesorplots youcreatedthathelpyouperformeachexercise.Thisdocumentshouldbesubmittedvia BlackboardnolaterthanmidnightFriday5/10/2019. In2004,thestateforNorthCarolinareleasedalargedatasetcontaininginformationonbirths recordedinthisstate.Thisdatasetisusefultoresearchersstudyingrelationbetweenhabits andpracticesofexpectantmothersandthebirthoftheirchildren.Wewillworkwitharandom sampleofobservationsfromthisdataset. TheData Wewillbeloadingthenc.csvdatasetintoourworkspace. 1. FromtheMyStatCrunchpage,locatethesectionMyData 2. Clickon“Selectafileonmycomputer”.Thiswillbringupanewwindow/tab 3. UsingtheChooseFilebuttontonavigatetothenc.csvonyourcomputer.Orusethe draganddropoption.Onceyou’veselectedtheCSV,apreviewofthefilewillappearon thescreen 4. Clicktheboxtousethefirstlineasthecolumnnames 5. EnsuretheDelimiterisComma(sincethefileisaCSV–CommaSeparatedValue). 6. ScrolltothebottomofthescreenandselectLoad.Anewtabwillopenwiththedata. Note:StatCrunchwillautomaticallysavethisfiletoMyDataforfutureuse;youdonot needtoloaditagain You’llseethatforeveryobservationwehave12variables,somecategoricalandsomenumeric. Themeaningofeachvariableisasfollows: Variable Description fage Father’sageinyears mage Mother’sageinyears mature Maturitystatusofmother weeks Lengthofpregnancyinweeks premie Whetherthebirthwasclassifiedaspremature(premie)orfull-term visits Numberofhospitalvisitsduringpregnancy marital Whethermotherismarriedornotmarriedatbirth gained Weightgainedbymotherduringpregnancyinpounds weight Weightofbabyatbirthinpounds lowbirthweight Whetherbabywasclassifiedaslowbirthweight(low)ornot(notlow) gender Genderofthebaby,maleorfemale habit Statusofthemotherasanonsmokerorasmoker ExploratoryAnalysis Let’sconsiderthepossiblerelationshipbetweenamother’ssmokinghabitandtheweightof herbaby.Plottingthedataisausefulfirststepbecauseithelpsusquicklyvisualizetrends, identifystrongassociationsanddevelopresearchquestions.Wewillcreateaside-byside boxplotforweightandhabit.Oneboxplotwilldescribethedistributionofweightforthose babiesborntonon-smokers.Thesecondboxplotwilldescribethedistributionofweightfor thosebabiesborntosmokers. Side-by-SideBoxplot: 1. Graph>Boxplot 2. Selectweightcolumn 3. IntheGroupBysection,choosehabitcolumn 4. EnsuretheGroupingOptionsare“Plotgroupsforeachcolumn” 5. ClickCompute Exercise1:Includetheside-by-sideboxplotyoujustcreated Theboxplotsshowhowthemediansofthetwodistributionscompare,butwecanalso comparethemeansusingthesummarystatisticfunctionwithagroupby. Group-BySummaryStatistics: 1. Stats>SummaryStats>Column 2. Selectweightcolumn 3. IntheGroupBysection,choosehabitcolumn 4. SelectthefollowingStatistics:n,Mean,StdDev 5. ClickCompute Exercise2:Includethesummarystatisticstableyoujustcreated Exercise3:Lookingattheboxplotsandthesummarystatisticstable,istherean observeddifferencebetweenthesetwodistributions? Inference Isthedifferenceweobservedstatisticallysignificant?Inordertoanswerthisquestion,wewill conductahypothesistest.Wewillusethet-distributionforthishypothesistest. Exercise4:Writethehypothesisfortestingiftheaverageweightsofbabiesbornto smokingandnon-smokingmothersaredifferent Beforewecontinue,weneedtofirstcheckthattheconditionsforinferencearemet.Recallthe inferenceconditionsforcomparingtwoindependentmeans: 1. Independence: § Withingroups:sampledobservationsmustbeindependent § Betweengroups:thetwogroupsmustbeindependentofeachother(non- paired) 2. SampleSize/Skew:Thedataisnotskewedorifmoderatelyskewedhasasufficiently largesamplesize. Exercise5:ExplainwhytheIndependenceconditionsaremet. Exercise6:Createhistogramsforbothdistributions.Usethesehistogramsandthe samplesizesyoucalculatedinExercise2toexplainwhytheSampleSize/Skew conditionsaresatisfied.Includethehistograms. Hint:CreateHistogramofweight variable,group-byhabit. NowwewilluseStatCrunchtocomputethestandarderror,teststatisticandp-valueforour hypothesistest. Let’sassignthosebabiesborntosmokerstoSample1.Andthosebabiesborntononsmokers willbeassignedtoSample2 HypothesisTest: 1. Stat>TStats>TwoSample>WithData 2. UnderSample1section,chooseweightcolumn 3. UnderSample1section,inthebuildthefollowingWherecondition:habit=“smoker” 4. UnderSample2section,chooseweightcolumn 5. UnderSample2section,inthebuildthefollowingWherecondition:habit= “nonsmoker” 6. InPerformsection,selectHypothesistestfor?" − ?$ 7. InPerformsection,setthenullvalueto0 8. InPerformsection,choose≠forthealternativehypothesis 9. IntheOptionalGraphsandTablessection,choosep-valueplot 10. ClickCompute Exercise7:IncludeboththeHypothesisTestResultstableandthep-valueplot Exercise8:Ata? = 0.05significanelevel,whatistheconclusionofthistest?Inother words,dowerejectorfailtorejectthenullhypothesis?Alsostateyourconclusionin plainlanguageinthecontextoftheresearchquestion. Nowwewillcomputeanequivalent,90%confidenceintervalandusethattoevaluateour hypothesis. ConfidenceInterval: 1. Stat>TStats>TwoSample>WithData 2. UnderSample1section,chooseweightcolumn 3. UnderSample1section,inthebuildthefollowingWherecondition:habit=“smoker” 4. UnderSample2section,chooseweightcolumn 5. UnderSample2section,inthebuildthefollowingWherecondition:habit= “nonsmoker” 6. InPerformsection,selectConfidenceIntervalfor?" − ?$ 7. InPerformsection,chooseconfidencelevelof0.90 8. ClickCompute Exercise9:Includethe90%confidenceintervalyoujustcalculated Exercise10:DoesthisconfidenceintervalsupportyourconclusionfromExercise8? Whyorwhynot? Exercise11:Interprettheconfidenceintervalyoujustfoundinthecontextofthe researchquestion. OnYourOwn Exercise12:Conductahypothesistestevaluatingwhethertheaverageweightgained byyoungermothersisdifferentthantheaverageweightgainedbymaturemothers. Includeyourhypothesis,testresultsandconclusions
Answered Same DayMay 07, 2021

Answer To: Microsoft Word - Math 119 Lab 3.docx Math119Lab3:InferencesforNumerical Data...

Pooja answered on May 08 2021
144 Votes
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From the box plot, it is evident that there is not much difference in the median weight of babies born to non-smoker and smoker
mother. The table of summary statistics indicates the same.  The average weight of babies born for non-smoker and smoker mother is 7.1 and 6.8 units respectively. The low value of variance for the weight of babies born to non-smoker and smoker mother indicates that their mean is reliable.
4)
Consider the null hypothesis, there is no significant difference in the average weight of babies born to smoking and non-smoking mothers. u1=u2.
The alternative hypothesis, there is a significant difference in the average weight of babies born to smoking and non-smoking mothers. u1=/=u2.
5)
The condition of Independence for within groups is met. This is because the different observation corresponds to different women.
The condition of Independence between the groups is met. This is because the two groups of smoking and non-smoking mothers are independent of each other.
From the box that I observed that the middle line of the box in the box plot lie in the middle of the box. Hence I can say that the distribution of the average weight of babies born for smoking and non-smoking mothers is approximately normally distributed. It is also evident that the sample size is large. Hence the central limit theorem can be applied in this case and the distribution...
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