Comparing Bayesian Statistics and Frequentist Statistics in Serious Games Research

Frequentist and Bayesian Statistics: a Critique

There are two broad approaches to formal statistical inference taken as concerned with the development of methods for analysing noisy empirical data and in particular as the attaching of measures of uncertainty to conclusions. The object of this paper is to summarize what is involved. The issue is this. We have data represented collectively by y and taken to be the observed value of a vector ra...

Bayesian Statistics BAYESIAN STATISTICS ∗

Mathematical statistics uses two major paradigms, conventional (or frequentist), and Bayesian. Bayesian methods provide a complete paradigm for both statistical inference and decision making under uncertainty. Bayesian methods may be derived from an axiomatic system, and hence provide a general, coherent methodology. Bayesian methods contain as particular cases many of the more often used frequ...

An Integrated Mathematical Statistics Primer: Objective Bayesian Construction, Frequentist Evaluation

Bayesian Statistics is typically taught, if at all, separately from conventional frequentist methods. It is becoming clear, however, that the emergence of powerful objective Bayesian methods (where the result, as in frequentist statistics, only depends on the assumed model and the observed data) provides a new unifying perspective on most established methods, and may be used in situations (e.g....

On the Foundations of Statistics: a Frequentist Approach on the Foundations of Statistics: a Frequentist Approach

A limited but basic problem in the foundations of statistics is the following: Given a para-metric model, given perhaps some observations from the model, but given no prior information about the parameters (\total ignorance"), what can we say about the occurrence of a speciied event A under this model in the future (prediction problem)? Or, as probabilities are often described in terms of bets,...

statistics in trauma research