![]() ![]() The Correlation and Covariance tools can both be used in the same setting, when you have N different measurement variables observed on a set of individuals. You can use the correlation analysis tool to examine each pair of measurement variables to determine whether the two measurement variables tend to move together - that is, whether large values of one variable tend to be associated with large values of the other (positive correlation), whether small values of one variable tend to be associated with large values of the other (negative correlation), or whether values of both variables tend to be unrelated (correlation near 0 (zero)). (For example, if the two measurement variables are weight and height, the value of the correlation coefficient is unchanged if weight is converted from pounds to kilograms.) The value of any correlation coefficient must be between -1 and +1 inclusive. Unlike the covariance, the correlation coefficient is scaled so that its value is independent of the units in which the two measurement variables are expressed.
0 Comments
Leave a Reply. |