Overview#

Implementation of the least squares method from scratch in R, solving the fundamental problem of finding the best-fit line (or hyperplane) through data points. The mathematical derivation and implementation demonstrate understanding beyond just calling library functions.

Key Concepts#

• Derived normal equations from calculus minimization
• Implemented matrix solution (AᵀAx = Aᵀb)
• Built visualization of fit quality
• Compared to R’s lm() for validation
• Extended to polynomial regression

Technologies#

R, Linear Algebra, Matrix Operations

Related Skills#

• R
• Mathematics
• Data Science