Explores linear regression, least squares, residuals, and confidence intervals in regression models.
Covers the basics of linear regression, OLS method, predicted values, residuals, matrix notation, goodness-of-fit, hypothesis testing, and confidence intervals.
Covers fundamental concepts in probabilities and statistics, including linear regression, exploratory statistics, and the analysis of probabilities.
Explores the linear regression model, OLS properties, hypothesis testing, interpretation, transformations, and practical considerations.
