Concept

Reduced chi-squared statistic

Related lectures (31)

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Chi-Square Test: Independence Hypothesis

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

Probabilistic Estimation in Spin Glass Card Game

Explores probabilistic estimation in the Spin Glass Card game, emphasizing room splitting based on a given parameter.

Estimation: Linear Estimator

Explores linear estimation, optimal criteria, and the orthogonality principle for good choices in estimation.

Consistency of Maximum Likelihood Estimation

Explores the mathematical reasoning behind the consistency of maximum likelihood estimation.

Probabilities and Statistics

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

Statistics Essentials: Chi-Square Test

Covers the Chi-square test to assess relationships between categorical variables through contingency tables.

Two-way ANOVA and Chi-square Test

Explores two-way ANOVA, chi-square test, model comparison, and variable transformation for statistical analysis.

Spectral Estimation: Gaussian vs Binary Signals

Explores spectral estimation for Gaussian and binary signals in the spiked matrix estimation problem, analyzing the impact of signal-to-noise ratio.

Linear Models: Basics

Introduces linear models in machine learning, covering basics, parametric models, multi-output regression, and evaluation metrics.

Finite element methods

Covers finite element methods for solving diffusion problems in porous media, including meshing, interpolation, and weighted residuals.

Estimation: Mean-Squared Error and Fisher Information

Explains estimation through mean-squared error and Fisher information in the context of adaptive filters and exponentiated distributions.

Model Selection: ROC Curves, Regression Evaluation, Conclusion

Explores thresholding, ROC curves, regression evaluation, naive methods, and model selection in machine learning.

Continuous Distributions: Testing and Estimation

Explores testing and estimating continuous distributions through interval partitioning and expected number calculations.

Statistical Tests: Independence and Homogeneity

Explores statistical tests for independence and homogeneity, including chi-square tests and Fisher's exact test, with practical examples and applications.

Basic Principles of Point Estimation

Explores the Method of Moments, Bias-Variance tradeoff, Consistency, Plug-In Principle, and Likelihood Principle in point estimation.

ANOVA: Partitioning Total SS

Covers ANOVA method, focusing on partitioning total sum of squares into treatment and error components, mean square calculations, Fisher statistic, and F-distribution.

Linear Regression: Basics

Covers the basics of linear regression, binary and multi-class classification, and evaluation metrics.

Linear Prediction and Filtering: Part 2

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Linear Least Squares: Minimizing Error Coefficients

Explores linear least squares, normal equations, and the importance of linear regression in minimizing errors.