Bayesian Statistics and Political Recruitment: A Comment

1976 ◽  
Vol 6 (1) ◽  
pp. 124-125
Author(s):  
Paul Whiteley
Keyword(s):  
Bayesian Statistics ◽  
Bayesian Approach ◽  
Subjective Probability ◽  
Analytical Techniques ◽  
Political Activism ◽  
Background Characteristics ◽  
Political Recruitment ◽  
Political Activist ◽  
The Individual ◽  
The Bayesian Approach

In an important contribution to the improvement of data analytical techniques in political science, Budge and Farlie examine the predictive success of various background characteristics in determining political activism [Ian Budge and Dennis Farlie, ‘Political Recruitment and Dropout’, this Journal, v (1975), 33–68]. The authors use the framework of Bayesian statistics, in which the subjective probability that a given individual will be a political activist is revised in the light of sample information about the background characteristics of activists to give a posterior (i.e. after the information or event) probability that the individual is an activist. Unfortunately, as the authors admit, they do not utilize fully all the components of the Bayesian approach.

scholarly journals Bayesian probabilities for occurrence of large earthquakes in the seismogenic sources of Japan and Phillipine during the period 1998-2017

2001 ◽  
Vol 34 (4) ◽  
pp. 1619
Author(s):  
T. M. TSAPANOS ◽  
O. CH. GALANIS ◽  
S. D. MAVRIDOU ◽  
M. P. HELMl
Keyword(s):  
Seismic Hazard ◽  
Bayesian Statistics ◽  
Poisson Distribution ◽  
Bayesian Approach ◽  
Seismic Sources ◽  
Time Interval ◽  
Seismogenic Sources ◽  
The One ◽  
Large Earthquakes ◽  
The Bayesian Approach

The Bayesian statistics is adopted in 11 seismic sources of Japan and 14 of Philippine in order to estimate the probabilities of occurrence of large future earthquakes, assuming that earthquakes occurrence follows the Poisson distribution. The Bayesian approach applied represents the probability that a certain cut-off magnitude (or larger) will exceed in a given time interval of 20 years, that is 1998-2017. This cut-off magnitude is chosen the one with M=7.0 or greater. In this case we can consider these obtained probabilities as a seismic hazard presentation. More over curves are produced which present the fluctuation of the seismic hazard between these seismic sources. These graphs of varying probability are useful either for engineering or other practical purposes

scholarly journals Principles of Statistical Inference: Likelihood and the Bayesian Paradigm

2010 ◽  
Vol 16 ◽  
pp. 1-18 ◽  
Author(s):  
Steve C. Wang
Keyword(s):  
Maximum Likelihood ◽  
Statistical Inference ◽  
Bayesian Approach ◽  
Subjective Probability ◽  
Prior Information ◽  
Maximum Likelihood Estimators ◽  
Likelihood Ratio Tests ◽  
Bayesian Paradigm ◽  
Point Estimators ◽  
The Bayesian Approach

We review two foundations of statistical inference, the theory of likelihood and the Bayesian paradigm. We begin by applying principles of likelihood to generate point estimators (maximum likelihood estimators) and hypothesis tests (likelihood ratio tests). We then describe the Bayesian approach, focusing on two controversial aspects: the use of prior information and subjective probability. We illustrate these analyses using simple examples.

Bayesian Statistics in Sociology: Past, Present, and Future

2019 ◽  
Vol 45 (1) ◽  
pp. 47-68 ◽  
Author(s):  
Scott M. Lynch ◽  
Bryce Bartlett
Keyword(s):  
Social Science ◽  
Bayesian Statistics ◽  
Bayesian Approach ◽  
Bayesian Methods ◽  
Bayes Theorem ◽  
Widespread Application ◽  
Software Packages ◽  
The Future ◽  
Direct Use ◽  
The Bayesian Approach

Although Bayes’ theorem has been around for more than 250 years, widespread application of the Bayesian approach only began in statistics in 1990. By 2000, Bayesian statistics had made considerable headway into social science, but even now its direct use is rare in articles in top sociology journals, perhaps because of a lack of knowledge about the topic. In this review, we provide an overview of the key ideas and terminology of Bayesian statistics, and we discuss articles in the top journals that have used or developed Bayesian methods over the last decade. In this process, we elucidate some of the advantages of the Bayesian approach. We highlight that many sociologists are, in fact, using Bayesian methods, even if they do not realize it, because techniques deployed by popular software packages often involve Bayesian logic and/or computation. Finally, we conclude by briefly discussing the future of Bayesian statistics in sociology.

Bayesian statistics

2010 ◽  
pp. 477-497
Author(s):  
Janet L. Peacock ◽  
Philip J. Peacock
Keyword(s):  
Bayesian Statistics ◽  
Bayesian Approach ◽  
Bayesian Methods ◽  
Posterior Distributions ◽  
Bayesian Analyses ◽  
Prior Distributions ◽  
Unknown Quantity ◽  
Frequentist Approach ◽  
Pros And Cons ◽  
The Bayesian Approach

Bayesian statistics 478 How Bayesian methods work 480 Prior distributions 482 Likelihood; posterior distributions 484 Summarizing and presenting results 486 Using Bayesian analyses in medicine 488 Software for Bayesian statistics 492 Reading Bayesian analyses in papers 494 Bayesian methods: a summary 496 In this chapter we describe the Bayesian approach to statistical analysis in contrast to the frequentist approach. We describe how Bayesian methods work including a description of prior and posterior distributions. We outline the role and choice of prior distributions and how they are combined with the data collected to provide an updated estimate of the unknown quantity being studied. We include examples of the use of Bayesian methods in medicine, and discuss the pros and cons of the Bayesian approach compared with the frequentist approach Finally, we give guidance on how to read and interpret Bayesian analyses in the medical literature....

scholarly journals Constraining absolute chronologies with the application of Bayesian analysis

ACTA IMEKO ◽  
2016 ◽  
Vol 5 (2) ◽  
pp. 14 ◽  
Author(s):  
Francesco Maspero ◽  
Emanuela Sibilia ◽  
Marco Martini
Keyword(s):  
Bayesian Analysis ◽  
Bayesian Statistics ◽  
Case Studies ◽  
Bayesian Approach ◽  
Common Language ◽  
Multiple Data ◽  
The Common ◽  
The Bayesian Approach

<p class="Abstract"><span lang="EN-US">In this work the application of Bayesian statistics to archaeological problems will be discussed. In particular, three case studies will be analyzed, each presenting complex interpretative scenarios, and the most suitable way to solve them. It will be shown that the Bayesian approach allows to refine a dating when in presence of multiple data, even from different dating techniques. The Bayesian approach is presented as the common language between physicists, archaeologists and statisticians to perform more accurate evaluations on stratigraphies and chronologies.</span></p>

Bayesian Inference

2021 ◽  
pp. 17-19
Author(s):  
Arnaud Dufays
Keyword(s):  
Bayesian Inference ◽  
Bayesian Statistics ◽  
Statistical Method ◽  
Bayesian Approach ◽  
Posterior Probability ◽  
Complex Problem ◽  
Sampling Techniques ◽  
Computational Power ◽  
Analytical Computation ◽  
The Bayesian Approach

This chapter evaluates Bayesian inference, which refers to the Bayesian statistical method for estimating the parameters of a model and for testing a hypothesis. It relies on subjective statistics and extensively uses Bayes’s theorem. In the early 1990s, Bayesian statistics boomed with the emergence of sampling techniques. These new tools rely on the computational power to sample from (rather than evaluate) the posterior probability. However, the main drawback of the Bayesian approach lies in the computation of the posterior probability. The analytical computation of the posterior probability is a complex problem for any application, and this has limited Bayesian statistics for years.

scholarly journals A very simple introduction to Bayesian statistics: From coin flips to insight

2020 ◽  
Author(s):  
Daniel Zuckerman
Keyword(s):  
Biological Sciences ◽  
Bayesian Analysis ◽  
Bayesian Statistics ◽  
Bayesian Approach ◽  
Prior Information ◽  
Model Parameters ◽  
Short Article ◽  
Absolute Minimum ◽  
Wet Lab ◽  
The Bayesian Approach

Bayesian statistical analyses are a growing part of the chemical and biological sciences for several reasons. Most importantly, the Bayesian approach of predicting underlying models based on data corresponds naturally with examination of complex systems, whether using wet-lab or computational means. The Bayesian structure also provides a systematic basis for estimating uncertainty in model parameters and permits incorporation of prior information in a quantitative and consistent way. While easy to state in words, these strengths of Bayesian analysis can be difficult to assimilate for beginners. This short article presents essential Bayesian concepts using very simple examples and the absolute minimum mathematics needed to maintain rigor.

scholarly journals The Bayesian Approach and the Results of the ISAR-REACT 5 Trial

2021 ◽  
Vol 14 (2) ◽  
pp. 231-232
Author(s):  
Adnan Kastrati ◽  
Alexander Hapfelmeier
Keyword(s):  
Bayesian Approach ◽  
The Bayesian Approach

scholarly journals Speciation of organosulfur compounds in carbonaceous chondrites

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Alexander Zherebker ◽  
Yury Kostyukevich ◽  
Dmitry S. Volkov ◽  
Ratibor G. Chumakov ◽  
Lukas Friederici ◽  
...  
Keyword(s):  
Organic Matter ◽  
Analytical Techniques ◽  
Ion Cyclotron Resonance ◽  
Organosulfur Compounds ◽  
Low Oxygen ◽  
Fticr Ms ◽  
Insoluble Organic Matter ◽  
Composition And Structure ◽  
Extractable Fraction ◽  
The Individual

AbstractDespite broad application of different analytical techniques for studies on organic matter of chondrite meteorites, information about composition and structure of individual compounds is still very limited due to extreme molecular diversity of extraterrestrial organic matter. Here we present the first application of isotopic exchange assisted Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) for analysis of alkali extractable fraction of insoluble organic matter (IOM) of the Murchison and Allende meteorites. This allowed us to determine the individual S-containing ions with different types of sulfur atoms in IOM. Thiols, thiophenes, sulfoxides, sulfonyls and sulfonates were identified in both samples but with different proportions, which contribution corroborated with the hydrothermal and thermal history of the meteorites. The results were supported by XPS and thermogravimetric analysis coupled to FTICR MS. The latter was applied for the first time for analysis of chondritic IOM. To emphasize the peculiar extraterrestrial origin of IOM we have compared it with coal kerogen, which is characterized by the comparable complexity of molecular composition but its aromatic nature and low oxygen content can be ascribed almost exclusively to degradation of biomacromolecules.

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