Statistical Justification of Least Squares

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (29)

Page 2 of 3

Linear Regression: Estimation and Inference

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

Logistic Regression: Classification

Covers supervised learning, classification using logistic regression, and challenges in optimization.

Linear Regression: Maximum Likelihood Approach

Covers linear regression topics including confidence intervals, variance, and maximum likelihood approach.

Linear Regression Basics

Covers the basics of linear regression, including OLS, heteroskedasticity, autocorrelation, instrumental variables, Maximum Likelihood Estimation, time series analysis, and practical advice.

Linear Regression Basics

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

Linear Regression: Regularization

Covers linear regression, regularization, and probabilistic models in generating labels.

Horseshoe Crabs: Logistic Regression Analysis

Explores logistic regression analysis of horseshoe crab data, focusing on odds ratio interpretation and model fitting.

Chimpanzee Data Analysis

Covers the analysis of chimpanzee data on learning times and explores generalized linear models and logistic regression.

Statistical Estimation Methods

Covers statistical estimation methods, including maximum likelihood and Bayesian estimation.

Linear Regression: Estimation and Testing

Explores linear regression estimation, hypothesis testing, and practical applications in statistics.