Covers linear regression basics, focusing on minimizing error using the principle of least squares and includes an ANOVA table and practical example in R.
Explores linear regression fundamentals, non-linear regression issues, and R-squared goodness of fit, with examples like Anscombe's quartet and the Datasaurus dataset.