Linear Regression Basics

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Related lectures (53)

Linear Regression Basics Log in to Mediaspace to watch this video

Introduces the basics of linear regression, covering OLS approach, residuals, hat matrix, and Gauss-Markov assumptions.

Maximum Likelihood Theory & Applications Log in to Mediaspace to watch this video

Covers maximum likelihood theory, applications, and hypothesis testing principles in econometrics.

Linear Regression: Beyond the Basics Log in to Mediaspace to watch this video

Explores advanced concepts in linear regression models, including multicollinearity, hypothesis testing, and handling outliers.

Instrumental Variables: Intuition and Estimation Log in to Mediaspace to watch this video

Covers instrumental variables, addressing endogeneity issues in regression analysis through estimation techniques and practical examples.

Linear Regression: Multicollinearity, Outliers, Model Specification Log in to Mediaspace to watch this video

Covers multicollinearity, outliers, model specification, and practical strategies in linear regression.

Linear Regression: Model Adjustment and Parameter Estimation Log in to Mediaspace to watch this video

Explains the decomposition of total sum of squares, model adjustment, and parameter estimation in linear regression.

Supervised Learning in Financial Econometrics Log in to Mediaspace to watch this video

Explores supervised learning in financial econometrics, covering linear regression, model fitting, potential problems, basis functions, subset selection, cross-validation, regularization, and random forests.

Linear Regression and Logistic Regression Log in to Mediaspace to watch this video

Covers linear and logistic regression for regression and classification tasks, focusing on loss functions and model training.

Linear Regression Model Log in to Mediaspace to watch this video

Explores the linear regression model, OLS properties, hypothesis testing, interpretation, transformations, and practical considerations.

Linear Regression: Basics and Applications Log in to Mediaspace to watch this video

Explores linear regression using the method of least squares to fit data points with the equation y = ax + b.

Machine Learning Fundamentals: Structure Discovery, Classification, Regression Log in to Mediaspace to watch this video

Covers fundamental machine learning concepts including Structure Discovery, Classification, and Regression.

Maximum Likelihood Estimation: Theory Log in to Mediaspace to watch this video

Covers the theory behind Maximum Likelihood Estimation, discussing properties and applications in binary choice and ordered multiresponse models.

Nonlinear Machine Learning: k-Nearest Neighbors and Feature Expansion Log in to Mediaspace to watch this video

Covers the transition from linear to nonlinear models, focusing on k-NN and feature expansion techniques.

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.

Understanding Data Attributes Log in to Mediaspace to watch this video

Covers the analysis of various data attributes and linear regression models.

Overfitting in Supervised Learning: Case Studies and Techniques Log in to Mediaspace to watch this video

Addresses overfitting in supervised learning through polynomial regression case studies and model selection techniques.

Regression: Interactive Lecture Log in to Mediaspace to watch this video

Covers linear regression, weighted regression, locally weighted regression, support vector regression, noise handling, and eye mapping using SVR.

Statistical Models and Parameter Estimation Log in to Mediaspace to watch this video

Explores statistical models, parameter estimation, and sampling distributions in probability and statistics.

Linear Models for Classification: Multi-Class Extensions Log in to Mediaspace to watch this video

Covers linear models for multi-class classification, focusing on logistic regression and evaluation metrics.

Least Squares Solutions Log in to Mediaspace to watch this video

Covers least squares solutions for linear systems using matrix operations and normal systems, illustrated with examples.

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