Bayesian statistics is becoming increasingly popular in a variety of disciplines, as technology catches up with the theory. In this volume of the Quantitative Research Kit, Mel Slater highlights the varieties of Bayesian analysis available to researchers, providing practical advice on how to apply these methods to data.
Bayesian statistics is becoming increasingly popular in a variety of disciplines, as technology catches up with the theory. In this volume of the Quantitative Research Kit, Mel Slater highlights the varieties of Bayesian analysis available to researchers, providing practical advice on how to apply these methods to data.
Mel Slater is a Distinguished Investigator at the University of Barcelona, and co-Director of the Event Lab (Experimental Virtual Environments for Neuroscience and Technology). He was previously Professor of Virtual Environments at University College London (UCL) in the Department of Computer Science. He was awarded the 2005 IEEE Virtual Reality Career Award: 'In Recognition of Pioneering Achievements in Theory and Applications of Virtual Reality'. He is Field Editor of Frontiers in Virtual Reality, and Chief Editor of the Human Behaviour in VR section. He was awarded the Humboldt Research Prize from Germany in 2020. He is a Fellow of the Royal Statistical Society.
Inhaltsangabe
Introduction A brief review of the necessary probability distributions and their relationships Statistical inference and estimation principles Simulation methods for Bayesian statistics The general linear model - Regression analysis. The exponential family Multivariate and Multilevel models Using Stata and JAGS for Bayesian Statistics
Introduction A brief review of the necessary probability distributions and their relationships Statistical inference and estimation principles Simulation methods for Bayesian statistics The general linear model - Regression analysis. The exponential family Multivariate and Multilevel models Using Stata and JAGS for Bayesian Statistics
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