Detection & Estimation

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Related lectures (31)

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Testing: t-tests

Covers t-tests, p-values calculation, and comparison of coefficients.

Probabilities and Statistics

Covers fundamental concepts in probabilities and statistics, including linear regression, exploratory statistics, and the analysis of probabilities.

Generalized Linear Models

Covers probability, random variables, expectation, GLMs, hypothesis testing, and Bayesian statistics with practical examples.

Introduction to Inference

Covers the basics of probability theory, random variables, joint probability, and inference.

Statistical Hypothesis Testing

Covers statistical hypothesis testing, likelihood estimation, and confidence intervals construction.

Classification Detection

Covers binary hypothesis testing and decision functions in specific scenarios.

Likelihood Ratio Test: Detection & Estimation

Covers the likelihood ratio test for detection and estimation in statistical analysis.

Probability and Statistics

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

Probability and Statistics: Fundamentals

Covers the fundamental concepts of probability and statistics, including interesting results, standard model, image processing, probability spaces, and statistical testing.

Confidence Intervals: Definition and Estimation

Explains confidence intervals, parameter estimation methods, and the central limit theorem in statistical inference.