Lectures related to Coefficient of multiple correlation

Copulas: Properties and Applications

Explores copulas in multivariate statistics, covering properties, fallacies, and applications in modeling dependence structures.

A Localization Tale: Practical Course by BIOP

Covers practical aspects of using Fiji for everyday tasks in biological imaging.

Linear Regression: Estimation and Inference

Explores linear regression estimation, linearity assumptions, and statistical tests in the context of model comparison.

Multivariate Statistics: Conditional Distributions

Covers conditional distributions and correlations in multivariate statistics, including partial variance and covariance, with applications to non-normal distributions.

Regression Analysis: Model Selection and Diagnostic Tools

Explores regression analysis tools, model selection, influential points, outliers, and diagnostic plots.

Regression Analysis: Interpretation and Applications

Explores multiple regression, ANOVA, interpretation of coefficients, and regression estimation.

Self-supervised learning

Explores self-supervised learning, embedding techniques, HSIC, and geometric information in downstream tasks.

Assessing Significance and Fit

Covers confidence intervals, R2, and examples on cement heat evolution and car horsepower-MPG relationships.

Canonical Correlation Analysis: Overview

Covers Canonical Correlation Analysis, a method to find relationships between two sets of variables.

Learning Strategies and Rewards

Explores hypothesis testing, mastery goals, student motivation, and the effects of rewards.

Linear Regression: Simple

Introduces simple linear regression, properties of residuals, variance decomposition, and the coefficient of determination in the context of Okun's law.

Gaussian Mixture Regression: Modeling and Prediction

Covers Gaussian Mixture Regression principles, modeling joint and conditional densities for multimodal datasets.

Multivariate Statistics: Normal Distribution

Covers the multivariate normal distribution, properties, and sampling methods.

Spatial Autocorrelation: Moran's I

Explores Moran's I for assessing spatial clustering in geographical data using precipitation as an example.

Model Selection Methods in Biostatistics

Explores model selection methods in biostatistics, emphasizing the importance of starting with a sensible model.

Dependence Measures: Rank Correlations

Covers rank correlations, tail dependence, and copula fitting methods.

Dependence Concepts and Copulas

Explores dependence concepts, copulas, correlation fallacies, and rank correlations in statistics.

Bivariate Data Analysis: Correlation and Regression

Explores bivariate data analysis, correlation, and regression techniques for model assessment.

Multilinear Regression: Least Square Fit

Explores multilinear regression, variance, correlation, optimization, ANOVA, and design procedures.

Four Functions Theorem Log in to Mediaspace to watch this video

Explores the Four Functions Theorem, covering positive correlation, XY2 inequality, and monotone increasing property.