Linear models: reversing the predictors and the predicted
Consider $n$ observed data points $(x_1,y_1),\dots, (x_n, y_n)$. We think they might satisfy a linear model $y = ax + b$. Finding the coefficients $a$ and $b$ is called linear regression, and the most typical way to find them is the method of least squares: that is, we find $a$ and $b$ that minimize the […]