On completion of the course, students should have acquired the following knowledge and skills: Combining and Bayesian and frequentist strategies for addressing and solving problems. Knowledge of the different elements in a problem of Bayseian inference, the different forms it may adopt and the ability to select a form from each specific problem. Knowledge of the advantages and disadvantages of Bayesian modelling as against frequentist modelling. Posing and solving analytically Bayesian inference problems in models based on exponential families and prior conjugate distributions. Posing and solving Bayesian inference problems with numerical methods in complex models
This book presents an account of the Bayesian and frequentist approaches to statistical inference. I...
This tutorial on Bayesian inference targets psychological researchers who are trained in the null hy...
An introductory lecture on Bayesian inference by Tracy A. Heath (http://phyloworks.org/). Some conte...
Bayesian Reasoning is both a fundamental idea of probability and a key model in applied sciences for...
University courses in elementary statistics are usually taught from a frequentist perspective. In th...
Students of statistics should be taught the ideas and methods that are widely used in practice and t...
This paper explores the why and what of statistical learning from a computational modelling perspect...
The methods of teaching statistical inference vary and too often, insufficient links are made to the...
A new book in the Econometric Exercises series, this volume contains questions and answers to provid...
This Bayesian modeling book is intended for practitioners and applied statisticians looking for a se...
On the basis of studying datasets of students' course scores, we constructed a Bayesian network and ...
Gerd Gigerenzer\u27s technique of frequency representations for solving the medical diagnosis proble...
There is a current emphasis on making the introductory statistics class more dataoriented. Data dist...
Bayesian analysts use a formal model, Bayes’ theorem to learn from their data in contrast to non-Bay...
Gerd Gigerenzer's technique of frequency representations for solving the medical diagnosis problem, ...
This book presents an account of the Bayesian and frequentist approaches to statistical inference. I...
This tutorial on Bayesian inference targets psychological researchers who are trained in the null hy...
An introductory lecture on Bayesian inference by Tracy A. Heath (http://phyloworks.org/). Some conte...
Bayesian Reasoning is both a fundamental idea of probability and a key model in applied sciences for...
University courses in elementary statistics are usually taught from a frequentist perspective. In th...
Students of statistics should be taught the ideas and methods that are widely used in practice and t...
This paper explores the why and what of statistical learning from a computational modelling perspect...
The methods of teaching statistical inference vary and too often, insufficient links are made to the...
A new book in the Econometric Exercises series, this volume contains questions and answers to provid...
This Bayesian modeling book is intended for practitioners and applied statisticians looking for a se...
On the basis of studying datasets of students' course scores, we constructed a Bayesian network and ...
Gerd Gigerenzer\u27s technique of frequency representations for solving the medical diagnosis proble...
There is a current emphasis on making the introductory statistics class more dataoriented. Data dist...
Bayesian analysts use a formal model, Bayes’ theorem to learn from their data in contrast to non-Bay...
Gerd Gigerenzer's technique of frequency representations for solving the medical diagnosis problem, ...
This book presents an account of the Bayesian and frequentist approaches to statistical inference. I...
This tutorial on Bayesian inference targets psychological researchers who are trained in the null hy...
An introductory lecture on Bayesian inference by Tracy A. Heath (http://phyloworks.org/). Some conte...
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