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Suppose that the values of y are generated by the following equation: y = a+Bxte Where a and B are unknown parameters and e is the random error. The table below gives the observed values of y and x for a sample of size 4. obs y X YA VB UA UB 1 40 2 2 15 3 3 50 7 4 35 9 Consider two different regression estimates (labeled A and B) of the unknown parameters a and B: 10 aB 20 A BA 4 BB 2 In the table above, do the following: (a) Fill in the predicted values of DA and VB corresponding to the four observed x values (2, 3, 7, 9). (b) Calculate the residuals UA and UB and add them to the table. In the chart below, do the following: (c) Plot and label the four observations ( .1 , .2 , 3 , and .4). Be sure to make the markers big enough to see clearly. (d) Carefully draw the two estimated regression lines, label them ya and DB. (e) Based on the values in the table and your chart, which of the two estimated regression lines (A or B) provides a better fit to the observed data based on the least-squares criterion. In other words, which set of estimates has a lower sum of squared residuals (SSR)