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Kingston, Ontario
Decision theory and Bayesian inference; principles of optimal statistical procedures; maximum likelihood principle; large sample theory for maximum likelihood estimates; principles of hypotheses testing and the Neyman-Pearson theory; generalized likelihood ratio tests; the chi-square, t, F and other distributions.
David Kong - 2014-07-31 04:04:04
A Fall 2013 Lin
The name of the course says it all. It's just the fundamentals, nothing really too complicated. Just do some n-dimensional matrix algebra here, use quadruple summation lines there. Terms like "sufficient statistics" and "complete statistics" come up a lot. How hard can that be? Oh and know the Greek alphabet! |
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