Answer:
3.04
Step-by-step explanation:
Given the prediction equation:
y_hat = 145.5 -5.5*x
- - - - x - - - - - - - - - у
1 - - 10.36 - - - - 87.87
2 - - 9.96 - - - - 89.83
3 - - 12.50 - - - - 71.61
1) y_hat = 145.5 -5.5*(10.36)
y_hat = 145.5 - 56.98 = 88.58
2) y_hat = 145.5 -5.5*(9.96)
y_hat = 145.5 - 54.78 = 90.72
3) y_hat = 145.5 -5.5*(12.50)
y_hat = 145.5 - 68.75 = 76.75
Root mean squared error (RMSE) :
Number of observations (n) = 3
√(Σ(y_hat - y)^2) / n
y_hat = predicted value
y = actual value
Σ[(88.58-87.87)^2+(90.72-89.83)^2+(76.75-71.61)]
Σ(0.71^2) + (0.89^2) + (5.14^2)
27.7158 / 3 = 9.2386
√9.2386
= 3.0395065
= 3.04
