1. Regression Line  R 2 represents the fraction of variation in the data (regression line)

2. 1-2 Statistics: The equation for the Pearson product moment correlation coefficient, r, is

3. Quantitative Methods: Causal Models Table 1: Franchise Population (000)Sales ($000) 150200 225150 314210 476240 588400 635200 785410 8110500 995610 1021120 1130190 1244180  Sales = 50.30 + 4.17 x Population  R 2 represents the fraction of variation in the data (regression line)  If R 2 = 1  data fits perfectly, here R 2 = 0.7744  good  Predicted Sales (95) = 50.30 + 4.17 x 95 = 446.45 not 610 (+164.55)  Predicted Sales (76) = 50.30 + 4.17 x 76 = 367.22 not 240 (-127.22)  Predicted Sales (14) = 50.30 + 4.17 x 14 = 108.68 not 210 (+101.32)

4. Unexplainable part always left – the random component Understand the process that causes demand