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 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.
