Introduction to Behavior Modeling: Simple Example

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Explores Bayesian methods in choice modeling for personalized menu optimization and individual choice prediction.

Introduces behavior modeling through a simple example, focusing on analyzing the market for electric cars.

Covers the development of a model to identify stable causal relationships between variables.

Explores maximum likelihood inference, model selection, and comparing models using likelihood ratios.

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

Explores mixture models, including discrete and continuous mixtures, and their application in capturing taste heterogeneity in populations.

Covers maximum likelihood theory, applications, and hypothesis testing principles in econometrics.

Explores bias, variance, and confidence intervals in parameter estimation using examples and distributions.

Explores the measurement and operationalization of outcomes in managing fever in children under five through examples and data collection approaches.

Covers Hidden Markov Models (HMM) for modeling time series data and decoding using the Viterbi Algorithm.