Question

A new car dealer has been using a naïve forecast to forecast weekly new car sales. Given the data below and the naïve forecast (need to provide), calculate the forecast error MSE.

Period	Demand	Forecast	Error (A-F)	Error2
1	57	-	-	-
2	62	57	-5	25
3	58	62	+4	16
4	60	58	-2	4
5	60	60	0	0
6	56	60	+4	16

Answer 1

From the given question, I assume you would just need to calculate MSE for the forecase data given.

So,

MSE or mean squared error is the most common metric for gauging error in forecasting method.

MSE is calculated by squaring the sum of absolute error value and dividing it by the number of observations.

Taking the dataset in excel and calculating the sum of Error^2, we have:

Thus we get the output as:

Now, we know the number of observations in this case is 6. So, we divide the sum of error^2 by 6 and get the MSE Value.

Thus, MSE = 61/6 = 10.16