7.410 Applied Statistics
Provides an introduction to modern applied statistics. Topics include likelihood-based methods for estimation, confidence intervals, and hypothesis-testing; bootstrapping; time series modeling; linear models; nonparametric regression; and model selection. Organized around examples drawn from the recent literature.
This class has no prerequisites.
7.410 will be offered this semester (Spring 2019). It is instructed by A. Solow.
Lecture occurs 2:30 PM to 4:00 PM on Tuesdays and Thursdays in 54-823.
This class counts for a total of 12 credits.
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