We shall follow the
growth of probability theory and applications from the 1650s onwards, in
parallel with the development of statistical inference. Bayesian,
Neyman-Pearson hypothesis testing and Fisherian likelihood methods will all be
covered, with an emphasis on relating theory to a wide range of
applications. Practical sessions will use SciPy and feature
closed-form solutions, iterative and Monte Carlo simulation methods.
We shall follow the
growth of probability theory and applications from the 1650s onwards, in
parallel with the development of statistical inference. Bayesian,
Neyman-Pearson hypothesis testing and Fisherian likelihood methods will all be
covered, with an emphasis on relating theory to a wide range of
applications. Practical sessions will use SciPy and feature
closed-form solutions, iterative and Monte Carlo simulation methods.
We shall follow the
growth of probability theory and applications from the 1650s onwards, in
parallel with the development of statistical inference. Bayesian,
Neyman-Pearson hypothesis testing and Fisherian likelihood methods will all be
covered, with an emphasis on relating theory to a wide range of
applications. Practical sessions will use SciPy and feature
closed-form solutions, iterative and Monte Carlo simulation methods.
We review recent breakthroughs in understanding
some general features of the Renormalization Group and of Quantum Field Theory.
We discuss some applications of these new results and their deep connection to
the entanglement of the Quantum Field Theory vacuum.