# Calculating Covariance Matrix, Regression Analysis

The question I'm trying to do considers the model $Y = \theta_{0} + \theta_{1} X +\theta_{2} X^2 + \epsilon$ and asks to compute the Covariance Matrix of the standard LSE.
So far I've found that $\hat\theta = (2, 0.8, 1)^T$ from the data we've been given. How do I then go about and construct the Covariance Matrix?