Because scores with a range on one variable are related to scores within a range on another variable, predictions can be made. The type of analysis is dependent on type of data gathered. Analysis of subgroups can often yield better data than analysis of whole. The correlational coefficient tells strength and direction of relationship. The larger then number, the more the variables consistently move together.
Common variance is the square of the correlational coefficient.
Within a population, this is often the case, but may not be true of a sample. A negative skew trails off to the lower end, which pulls the mean and median towards the lower side. The farther apart the mean and median, the more the distribution is skewed. This allows us to average scores from various tests. Assumes normal distribution, and test for specific population.