It is common in the behavioral sciences to observe a perfect linear relationship between two variables.
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Q94: In the case of a perfect negative
Q95: The standard error of estimate is an
Q96: In the regression equation, Q97: Which correlation coefficient most closely represents the Q98: In the case of a positive or Q100: The general form of the linear model Q101: A sum of squares indicates the extent 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
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