The article discusses how statisticians use the multivariate normal distribution to analyze data with known covariance. They find that the distribution forms ellipsoids around the mean, with each component having a normal distribution. The posterior precision matrix is calculated by combining prior and observation matrices. The probability of all components being within credible intervals simultaneously is low. Independent priors for each parameter do not work together as conjugate priors.