Answer:
0.6
Explanation:
Given the regression equation :
y = 0.2x + 3,
The actual value of y when x = 5 is 4.6
The predicted of y using the model when x = 5 is :
Put x = 5 in the equation :
y = 0.2(5) + 3
y = 1 + 3
y = 4
The error in the value of y predicted is :
Error = Actual value - Predicted value
Error = 4.6 - 4
Error = 0.6