Polymer Modeling: Interactions and Scaling Behavior

Related lectures (30)

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Explores the concept of end-to-end vector and its practical implications.

Explores how instrumental variables correct biases from measurement error and reverse causality in regression models.

Covers the theory and practical applications of linear regression.

Explores continuous random variables, density functions, and distribution laws with practical examples.

Covers continuous random variables, probability density functions, and distributions, with practical examples.

Covers joint probability distributions for dependent random variables and how to estimate joint probabilities.

Explores joint random variables, conditional density, and independence in probability and statistics.

Covers graphical models for probabilistic distributions using graphs, nodes, and edges.

Explores glass and melting transitions in polymers, including characterization methods and specific polymer properties.

Explores maximum likelihood inference, comparing models based on likelihood ratios and demonstrating with a coin example.