Course: Essentials of Probability and Statistical Inference IV

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Essentials of Probability and Statistical Inference IV

Course

Instructor:

Rafael Irizarry

Originally Offered :

Spring 2006

Offered By:

Biostatistics

Course Number:

140.649



Description:

Introduces the theory and application of modern, computationally-based methods for exploring and drawing inferences from data. Covers re-sampling methods, non-parametric regression, prediction, and dimension reduction and clustering. Specific topics include Monte Carlo simulation, bootstrap cross-validation, splines, local weighted regression, CART, random forests, neural networks, support vector machines, and hierarchical clustering. De-emphasizes proofs and replaces them with extended discussion of interpretation of results and simulation and data analysis for illustration.