Hi, I am confused with respect to these two terms. In a book on regression analysis, I read the following statements. 1. For two normally distributed variables, zero covariance / correlation means independence of the two variables. 2. With the normality assumption, the following equation means that [tex] \mu_i [/tex] and [tex] \mu_j [/tex] are NOT ONLY uncorrelated BUT ALSO independently distributed. [tex] \left \mu_i - N (0, \sigma^2 \right) [/tex] Not able to get the wiggly line (~) after ui I am trying to understand if it is possible to have two variables that are (a) uncorrelated, and not-independent. (b) uncorrelated and independent (c) correlated and not-independent (d) correlated and independent I would appreciate it if you could explain each type with one example. Thanks MG.