The _________________ tells us how much of the percentage change in the dependent variable (Y) is explained by the percentage change in the independent variable (X) for a causal forecasting model. standard error correlation coefficient coefficient of determination slope of the regression line
Added by Lisa Y.
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Step 1: The coefficient of determination, denoted as \( R^2 \), is a measure of how well the independent variable (X) explains the variability of the dependent variable (Y) in a regression model. Show more…
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The correlation coefficient is: the range of values over which the probability may be estimated based upon the regression equation results. the proportion of the total variance in the dependent variable explained by the independent variable. the measure of variability of the actual observations from the predicting (forecasting) equation line. the relative degree that changes in one variable can be used to estimate changes in another variable.
Ishana K.
In the simple linear regression model, the regression slope indicates by how many percent Y increases, given a one percent increase in X. when multiplied with the explanatory variable will give you the predicted Y. indicates by how many units Y increases, given a one unit increase in X. represents the elasticity of Y on X.
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Use the value of the correlation coefficient $r$ to calculate the coefficient of determination $r^{2}$. What does this tell you about the explained variation of the data about the regression line? About the unexplained variation? $$r=-0.957$$
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