Variance, Covariance Matrix, Linear Regression, Standard Error, Confidence Interval.
assumption allows us to estimate the sum of squares of errors using the sum of squares of residuals. In other words: e’e as an unbiased estimator of the sum of squares of regression errors (Image by Author) Let’s once again revisit the linear regression model. In order to fit the model on a sample