(2011), Bayesian ideas and data analysis, Chapman and Hall.Christensen, R et al, 2011, Bayesian Ideas and Data Analysis, ed. 1, Taylor & Francis Group, New York.Christensen, R., Johnson, W. O., Branscum, A. J.
E. (2011). Bayesian ideas and data analysis: An introduction for scientists and statisticians. Boca Raton, FL: Chapman & Hall.Christensen, R., Johnson, W., Branscum, A., and Hanson, T.: Bayesian ideas and data analysis: An introduction for scientists and statisticians, CRC, 2010. 5138 ...
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The first section of the article explains the foundational ideas of Bayesian methods, and shows how those ideas already match your intuitions from everyday reasoning and research. The next sections show some simple examples of Bayesian data analysis, for you to see how the information delivered by...
variation around a central tendency. The central tendencies of the groups are conceptualized as deflections from an overall baseline. Details of this model were introduced back inSection 15.2.4.1(p. 429), and illustrated inFigure 15.4(p. 431). The ideas are briefly recapitulated in the following...
A Bayesian model for this design is shown inFigure 2. The essential ideas are simple: the accuracy observed for each individual in the shift phase is assumed to reflect the underlying true accuracy for that individual, and individual accuracy values are assumed to come from a distribution determi...
Bayesian ideas already match your intuitions from everyday reasoning and from traditional data analysis. Simple examples of Bayesian data analysis are presented that illustrate how the information delivered by a Bayesian analysis can be directly interpreted. Bayesian approaches to null-value assessment ...
The Bayesian brain hypothesis is one of the most influential ideas in neuroscience. However, unstated differences in how Bayesian ideas are operationalized make it difficult to draw general conclusions about how Bayesian computations map onto neural circuits. Here, we identify one such unstated differe...
We then switch to the practical realization of this analysis framework in terms of Markov Chains. A brief review of Markov Chains is given, followed by a discussion of the implementation in BAT. We then give examples of parameter estimation to make the ideas more concrete....
This book provides a multi-level introduction to Bayesian reasoning (as opposed to “conventional statistics”) and its applications to data analysis. The basic ideas of this “new” approach to the quantification of uncertainty are presented using examples from research and everyday life. Application...