Statistical Inference

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Related lectures (57)

Generalized Linear Models: A Brief Review Log in to Mediaspace to watch this video

Provides an overview of Generalized Linear Models, focusing on logistic and Poisson regression models, and their implementation in R.

Eigenstate Thermalization Hypothesis Log in to Mediaspace to watch this video

Explores the Eigenstate Thermalization Hypothesis in quantum systems, emphasizing the random matrix theory and the behavior of observables in thermal equilibrium.

Conditional Probability: Definition and Examples Log in to Mediaspace to watch this video

Explains the calculation of conditional probability with definitions and examples.

Expectation Maximization: Learning Parameters Log in to Mediaspace to watch this video

Covers the Expectation Maximization algorithm for learning parameters and dealing with unknown variables.

Applications of Quantum Science: Densities and Statistics Log in to Mediaspace to watch this video

Covers the applications of densities and statistics in quantum science, focusing on binomial and Poisson distributions.

L-Moment Estimation: Probability-Weighted Moments Log in to Mediaspace to watch this video

Covers L-moment estimation, probability-weighted moments, and maximum likelihood inference basics.

Log-Concave Functions Log in to Mediaspace to watch this video

Covers the concept of log-concave functions and their implications in probability distributions and Gaussian correlation inequalities.

Extreme Value Theory: Applications and Threshold Selection Log in to Mediaspace to watch this video

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

Poisson Process: Density Theory and Applications Log in to Mediaspace to watch this video

Explores Poisson processes, joint density, independence of events, and likelihood estimation.

Important Sampling: Monte Carlo Estimation Log in to Mediaspace to watch this video

Covers important sampling for efficient Monte Carlo estimation of expected values using a new distribution to reduce variance.

Gaussian Mixture Models & Noisy Signals Log in to Mediaspace to watch this video

Explores Gaussian mixture models and denoising noisy signals using a probabilistic approach.

General Linear Model: Model Selection Log in to Mediaspace to watch this video

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

Central Limit Theorem Log in to Mediaspace to watch this video

Covers the central limit theorem, showing how random processes converge to a normal distribution.

Dispersion Models: Understanding Axial Dispersion Coefficient Log in to Mediaspace to watch this video

Explores dispersion models and the axial dispersion coefficient in fluid systems.

Untitled Log in to Mediaspace to watch this video

Data Analysis Techniques: Amplitude Shift Keying and Graphical Methods Log in to Mediaspace to watch this video

Covers amplitude shift keying and various data analysis techniques using Jupyter Notebooks.

Linear Regression Basics Log in to Mediaspace to watch this video

Covers the basics of linear regression, instrumental variables, heteroskedasticity, autocorrelation, and Maximum Likelihood Estimation.

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