Linear Regression: Confidence Bounds

Explores linear regression, least squares, residuals, and confidence intervals in regression models.

Covers key assumptions, variance analysis, and confidence intervals in linear regression.

Covers bivariate data analysis, correlation, and regression techniques, including interpretation of coefficients and least squares geometry.

Covers point estimation, confidence intervals, and hypothesis testing for smooth functions using mixed models and spline smoothing.

Delves into linear regression, emphasizing least squares estimation, residuals, and variance.