A sum of squares indicates the extent to which two sets of scores vary from one another,or covary.
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Q96: In the regression equation, Q97: Which correlation coefficient most closely represents the Q98: In the case of a positive or Q99: It is common in the behavioral sciences Q100: The general form of the linear model Q102: If X helps to predict Y,then the Q103: The absolute magnitude of the standard error Q104: The formula for computing the intercept is Q105: When there is no linear relationship between Q106: When two variables are not perfectly correlated,the
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