Answer:
9
Step-by-step explanation:
The mean squared error (MSE)of a set of observations can be calculated using the formula :
(1/n)Σ(Actual values - predicted values)^2
Where n = number of observations
Steps :
Error values of each observation (difference between actual and predicted values) is squared.
Step 2:
The squared values are summed
Step 3:
The summation is the divided by the number of observations
The difference between the actual and predicted values is known as the ERROR.
(1/n)Σ(ERROR)^2
n = 3
Error = +3, +3, - 3
MSE = (1/3)Σ[(3)^2 + (3)^2 + (-3)^2]
MSE = (1/3) × [9 + 9 + 9]
MSE = (1/3) × 27
MSE = 9
