The covariance matrix

CORRECTION: At https://www.seevid.ir/fa/w/WBlnwvjfMtQ we shouldn't divide by 4 to get the covariance, we should divide by 1+1+1+1/3, which is 10/3. That means the covariances are the following: Var(x) = 1.056 Var(y) = 0.864 Cov(x,y) = 0.768 (Thank you Shivkumar Pippal!) Mean, variance, covariance, and the covariance matrix for a dataset and a weighted dataset. Announcement: Book by Luis Serrano! Grokking Machine Learning. bit.ly/grokkingML 40% discount code: serranoyt https://www.seevid.ir/fa/w/WBlnwvjfMtQ Introduction https://www.seevid.ir/fa/w/WBlnwvjfMtQ The covariance matrix https://www.seevid.ir/fa/w/WBlnwvjfMtQ Average https://www.seevid.ir/fa/w/WBlnwvjfMtQ X-variance https://www.seevid.ir/fa/w/WBlnwvjfMtQ Problem: Same variances https://www.seevid.ir/fa/w/WBlnwvjfMtQ Formulas https://www.seevid.ir/fa/w/WBlnwvjfMtQ Center points