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Related lectures (32)

Stochastic Simulation: Introduction and G/G/1 Queueing Model

Covers the stochastic simulations course, G/G/1 queueing model, computational finance, statistics, physics, and Bayesian inference.

Non nested hypotheses

Covers the comparison of restricted and unrestricted choice models using the likelihood ratio test and the Cox test.

Extreme Value Theory: Applications and Threshold Selection

Explores extremal limit theorems, applications like Vargas rainfall data, and fitting piecewise Generalized Pareto Distributions.

Bayesian Statistics: Hypothesis Testing and Estimation

Covers hypothesis testing, p-values, significance levels, and Bayesian estimation.

Chi-Square Test: Independence Hypothesis

Explains the Chi-Square test for independence hypothesis and its practical applications.

General Linear Model: Model Selection

Explores the General Linear Model, significance testing, model selection, and parameter inference.

Logistic Regression: Model Interpretation and Comparison

Explores logistic regression model interpretation, parameter estimation, and model comparison using likelihood ratio tests.

Generalised Linear Models: Regression with Exponential Family Responses

Covers regression with exponential family responses using Generalised Linear Models.

Likelihood Ratio Test

Covers the Likelihood Ratio Test in choice models, comparing unrestricted and restricted models through benchmarking and testing different model specifications.

DOE Qualitative factors: IV

Explores qualitative factors in Design of Experiments, including statistical tests and error types.

Likelihood Ratio Test: Neyman-Pearson Lemma

Explores likelihood ratio tests and the Neyman-Pearson Lemma for statistical hypothesis testing.

Testing: Likelihood Ratio Test

Covers the likelihood ratio test in choice models, benchmarking, and tests for taste variations and nonlinear specifications.

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