Interpreting Simple Linear Regression 1. Linear correlation coefficient r = 0.794556 2. Coefficient of Determination ( r square) 0.631319 3. Standard Error of the estimate = 12.9668 4. SSR (Explained variation) = 5182.41 5. SSE ( Unexplained variation) = 3026.49 6. SST = 8208.90 7. Predicted equation or equation of the regression line (Y predicted or hat) = 0.725983X + 16.5523 8. Level of Significance = 0.1 9. Critical Value= 0.378419 Question What is meant by SSR? Which number measures the variation explained by the regression line?   Sum of the Squares Regression (SSR); amount of variation in Y explained by the variation in X explanatory variable   Sum of the Squares Regression (SSR); amount of variation in X explained by the variation in Y   SSR is the percent variation in total variation SST that is explained by the variation in X or SSR/SST = 5182.41/8208.90 = 0.631319 or 63%   Both A and C

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Interpreting Simple Linear Regression

1. Linear correlation coefficient r = 0.794556

2. Coefficient of Determination ( r square) 0.631319

3. Standard Error of the estimate = 12.9668

4. SSR (Explained variation) = 5182.41

5. SSE ( Unexplained variation) = 3026.49

6. SST = 8208.90

7. Predicted equation or equation of the regression line (Y predicted or hat) = 0.725983X + 16.5523

8. Level of Significance = 0.1

9. Critical Value= 0.378419

Question

What is meant by SSR? Which number measures the variation explained by the regression line?

 
  1. Sum of the Squares Regression (SSR); amount of variation in Y explained by the variation in X explanatory variable

     
  2. Sum of the Squares Regression (SSR); amount of variation in X explained by the variation in Y

     
  3. SSR is the percent variation in total variation SST that is explained by the variation in X or SSR/SST = 5182.41/8208.90 = 0.631319 or 63%

     
  4. Both A and C

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