Shanti wrote the predicted values for a data set using the line of best fit y = 2.55x – 3.15. she computed two of the residual values. what are the values of a and b? a = 0.4 and b = –0.15 a = –0.4 and b = 0.15 a = 8.6 and b = 14.25 a = –8.6 and b = –14.25

Residual value is the difference between the observed value of the dependent variable (y) and the predicted value (ŷ) in a data set.

i.e. Residual value = given value - predicted value

From the table, the residual value corresponding to a has 4.1 as the given value and 4.5 as the predicted value.
Therefore, a = 4.1 - 4.5 = -0.4

Similarly, the residual value corresponding to b has 7.2 as the given value and 7.05 as the predicted value.
Therefore, b = 7.2 - 7.05 = 0.15

Therefore, a = -0.4 and b = 0.15