On rules of induction and the raven paradox in Bayesian confirmation theory

2014 ◽  
Author(s):  
H. M. Afshar ◽  
P. Sunehag
Keyword(s):  
Confirmation Theory ◽  
Bayesian Confirmation Theory ◽  
Bayesian Confirmation ◽  
Raven Paradox

Bayesian belief updating after a replication experiment

2018 ◽  
Vol 41 ◽  
Author(s):  
Alex O. Holcombe ◽  
Samuel J. Gershman
Keyword(s):  
Confirmation Theory ◽  
Bayesian Confirmation Theory ◽  
Belief Updating ◽  
Original Experiment ◽  
Bayesian Confirmation ◽  
Replication Experiment

AbstractZwaan et al. and others discuss the importance of the inevitable differences between a replication experiment and the corresponding original experiment. But these discussions are not informed by a principled, quantitative framework for taking differences into account. Bayesian confirmation theory provides such a framework. It will not entirely solve the problem, but it will lead to new insights.

scholarly journals The Problem of New Evidence: P-Hacking and Pre-Analysis Plans

Diametros ◽  
2020 ◽  
pp. 1-24
Author(s):  
Zoe Hitzig ◽  
Jacob Stegenga
Keyword(s):  
Model Selection ◽  
Policy Option ◽  
Confirmation Theory ◽  
Bayesian Confirmation Theory ◽  
Bayesian Confirmation ◽  
Selection Theory ◽  
New Evidence ◽  
Theory And Model

We provide a novel articulation of the epistemic peril of p-hacking using three resources from philosophy: predictivism, Bayesian confirmation theory, and model selection theory. We defend a nuanced position on p-hacking: p-hacking is sometimes, but not always, epistemically pernicious. Our argument requires a novel understanding of Bayesianism, since a standard criticism of Bayesian confirmation theory is that it cannot represent the influence of biased methods. We then turn to pre-analysis plans, a methodological device used to mitigate p-hacking. Some say that pre-analysis plans are epistemically meritorious while others deny this, and in practice pre-analysis plans are often violated. We resolve this debate with a modest defence of pre-analysis plans. Further, we argue that pre-analysis plans can be epistemically relevant even if the plan is not strictly followed—and suggest that allowing for flexible pre-analysis plans may be the best available policy option.

scholarly journals Coherence and Reduction

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Andrea Giuseppe Ragno
Keyword(s):  
Statistical Mechanics ◽  
Confirmation Theory ◽  
Bayesian Confirmation Theory ◽  
Numerical Examples ◽  
Bayesian Confirmation ◽  
Degree Of Coherence ◽  
Confirmation Measures ◽  
Before And After ◽  
Important Field ◽  
Scientific Reduction

Abstract Synchronic intertheoretic reductions are an important field of research in science. Arguably, the best model able to represent the main relations occurring in this kind of scientific reduction is the Nagelian account of reduction, a model further developed by Schaffner and nowadays known as the generalized version of the Nagel–Schaffner model (GNS). In their article (2010), Dizadji-Bahmani, Frigg, and Hartmann (DFH) specified the two main desiderata of a reduction á la GNS: confirmation and coherence. DFH first and, more rigorously, Tešic (2017) later analyse the confirmatory relation between the reducing and the reduced theory in terms of Bayesian confirmation theory. The purpose of this article is to analyse and compare the degree of coherence between the two theories involved in the GNS before and after the reduction. For this reason, in the first section, I will be looking at the reduction of thermodynamics to statistical mechanics and use it as an example to describe the GNS. In the second section, I will introduce three coherence measures which will then be employed in the comparison. Finally, in the last two sections, I will compare the degrees of coherence between the reducing and the reduced theory before and after the reduction and use a few numerical examples to understand the relation between coherence and confirmation measures.

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