Linear Regression Math

Summary

Understanding the math behind fitting a line — minimizing squared error between predictions and actual values — before treating it as a black-box function call in a library.

• 1Derive (or follow a derivation of) the least-squares solution for simple linear regression.
• 2Fit a line by hand on a tiny dataset and compare it to a library's output.
• 3Learn to interpret a regression coefficient and intercept in plain language.