Variance, Covariance Matrix, Linear Regression, Standard Error, Confidence Interval.
Thus, the fitted model looks like this: The fitted linear model (Image by Author) In the above equation, e is the vector of residual errors (a.k.a. residuals). The residual e is the difference between the observed value of y and the value y_cap that is predicted by the fitted model. If the model is