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# Essentials of Probability and Statistical Inference IV: Algorithmic and NonParametic Approaches

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## Essentials of Probability and Statistical Inference IV: Algorithmic and NonParametic Approaches

This course 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... More
Material Type: Online Course
Technical Format: PDF
Date Added to MERLOT: July 18, 2008
Date Modified in MERLOT: February 08, 2012
Author:

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Primary Audience: Graduate School, Professional, College Upper Division
Mobile Compatibility: Not specified at this time
Language: English
Cost Involved: no
Source Code Available: unsure
Accessiblity Information Available: unsure
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