Abstract
The oscillation results presented in this thesis are to be interpreted in the Bayesian framework. This chapter starts with a brief discussion on Bayesian inference and Monte Carlo methods for sampling from multivariate posterior probability distributions. The probability distribution for oscillation parameters to take on certain values, given the collected T2K neutrino and anti-neutrino data, is also discussed. Finally, a summary of flux, cross section and detector inputs for the oscillation analysis has been presented.
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Notes
- 1.
Strictly speaking, the probability for data is unity, since it has already happened.
- 2.
Processes where the charge of the pion changes through scattering.
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Vladisavljevic, T. (2020). Bayesian Statistics and the Markov Chain Monte Carlo Technique for Neutrino Oscillation Analyses. In: Predicting the T2K Neutrino Flux and Measuring Oscillation Parameters. Springer Theses. Springer, Cham. https://doi.org/10.1007/978-3-030-51174-6_7
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