Covers the basics of linear regression, including OLS estimators, hypothesis testing, and confidence intervals.
Explores probabilistic linear regression, covering joint and conditional probability, ridge regression, and overfitting mitigation.
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.
Covers fundamental concepts in probability and statistics, emphasizing data analysis techniques and statistical modeling.
