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ExploratoryDataAnalysisUsingR2018
ExploratoryDataAnalysisUsingRprovidesaclassroom-testedintroductiontoexploratorydataanalysis(EDA)andintroducestherangeof"interesting"–good,bad,andugly–featuresthatcanbefoundindata,andwhyitisimportanttofindthem.ItalsointroducesthemechanicsofusingRtoexploreandexplaindata.Thebookbeginswithadetailedoverviewofdata,exploratoryanalysis,andR,aswellasgraphicsinR.Itthenexploresworkingwithexternaldata,linearregressionmodels,andcraftingdatastories.ThesecondpartofthebookfocusesondevelopingRprograms,includinggoodprogrammingpracticesandexamples,workingwithtextdata,andgeneralpredictivemodels.Thebookendswithachapteron"keepingitalltogether"thatincludesmanagingtheRinstallation,managingfiles,documenting,andanintroductiontoreproduciblecomputing.Thebookisdesignedforbothadvancedundergraduate,entry-levelgraduatestudents,andworkingprofessionalswithlittletonopriorexposuretodataanalysis,modeling,statistics,orprogramming.itkeepsthetreatmentrelativelynon-mathematical,eventhoughdataanalysisisaninherentlymathematicalsubject.Exercisesareincludedattheendofmostchapters,andaninstructor'ssolutionmanualisavailable.AbouttheAuthor:RonaldK.PearsonholdsthepositionofSeniorDataScientistwithGeoVera,apropertyinsurancecompanyinFairfield,California,andhehaspreviouslyheldsimilarpositionsinavarietyofapplicationareas,includingsoftwaredevelopment,drugsafetydataanalysis,andtheanalysisofindustrialprocessdata.HeholdsaPhDinElectricalEngineeringandComputerSciencefromtheMassachusettsInstituteofTechnologyandhaspublishedconferenceandjournalpapersontopicsrangingfromnonlineardynamicmodelstructureselectiontotheproblemsofdisguisedmissingdatainpredictivemodeling.Dr.Pearsonhasauthoredorco-authoredbooksincludingExploringDatainEngineeri
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