The hyperbolic arctangent of this value is used to test hypotheses about it, and is known as the Fisher transformation. For given sets A and B, this value is equal to the covariance of A and B divided by the product of the standard deviations of A an
The hyperbolic arctangent of this value is used to test hypotheses about it, and is known as the Fisher transformation. For given sets A and B, this value is equal to the covariance of A and B divided by the product of the standard deviations of A and B. The sampling distribution of this value follows an n minus 2 degrees of freedom t-distribution. An alternative to it is Spearman's rho, which is based on ranks. The square of this value is the amount of variation in the (*) dependent variable that can be explained by the independent variable in a least-squares regression. For a perfectly dependent pair of variables, it is equal to 1. For 10 points, identify this value developed by Pearson which measures how well a particular line fits a series of points.
The hyperbolic arctangent of this value is used to test hypotheses about it, and is known as the Fisher transformation.
R [or correlation; accept R-squared; accept Pearson's coefficient before mention]