Doing Bayesian Data Analysis, Second Edition: A Tutorial with R, JAGS, and Stan

DoingBayesianDataAnalysis:ATutorialwithR,JAGS,andStan,SecondEditionprovidesanaccessibleapproachforconductingBayesiandataanalysis,asmaterialisexplainedclearlywithconcreteexamples.Includedarestep-by-stepinstructionsonhowtocarryoutBayesiandataanalysesinthepopularandfreesoftwareRandWinBugs,aswellasnewprogramsinJAGSandStan.Thenewprogramsaredesignedtobemucheasiertousethanthescriptsinthefirstedition.Inparticular,therearenowcompacthigh-levelscriptsthatmakeiteasytoruntheprogramsonyourowndatasets.Thebookisdividedintothreepartsandbeginswiththebasics:models,probability,Bayes’rule,andtheRprogramminglanguage.Thediscussionthenmovestothefundamentalsappliedtoinferringabinomialprobability,beforeconcludingwithchaptersonthegeneralizedlinearmodel.Topicsincludemetric-predictedvariableononeortwogroups;metric-predictedvariablewithonemetricpredictor;metric-predictedvariablewithmultiplemetricpredictors;metric-predictedvariablewithonenominalpredictor;andmetric-predictedvariablewithmultiplenominalpredictors.Theexercisesfoundinthetexthaveexplicitpurposesandguidelinesforaccomplishment.Thisbookisintendedforfirst-yeargraduatestudentsoradvancedundergraduatesinstatistics,dataanalysis,psychology,cognitivescience,socialsciences,clinicalsciences,andconsumersciencesinbusiness.Accessible,includingthebasicsofessentialconceptsofprobabilityandrandomsamplingExampleswithRprogramminglanguageandJAGSsoftwareComprehensivecoverageofallscenariosaddressedbynon-Bayesiantextbooks:t-tests,analysisofvariance(ANOVA)andcomparisonsinANOVA,multipleregression,andchi-square(contingencytableanalysis)CoverageofexperimentplanningRandJAGScomputerprogrammingcodeonwebsiteExerciseshaveexplicitpurposesandguidelinesforaccomplishmentProvidesstep-by-stepinstructionsonhowtoconductBayesiandataanalysesinthepopularandfreesoftwareRandWinBugs