Question

Consider the following time series data.

Week	1	2	3	4	5	6
Value	18	14	16	12	17	14

Using the naive method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy. Round the intermediate calculations to two decimal places.

1. Mean absolute error (to 1 decimal).
   
2. Mean squared error (to 1 decimal).
   
3. Mean absolute percentage error (to 2 decimals).
   %
4. What is the forecast for week 7 (to the nearest whole number)?
   

Consider the following time series data.

Week	1	2	3	4	5	6
Value	18	13	17	11	17	15

Calculate the measures of forecast error using the naive (most recent value) method and the average of historical data (to 2 decimals).

	Naive method	Historical data
Mean absolute error
Mean squared error
Mean absolute percentage error

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Consider the following time series data.

Month	1	2	3	4	5	6	7
Value	23	14	19	10	18	23	26

Round your answers to two decimal places.

a. Compute MSE using the most recent value as the forecast for the next period.

Mean squared error is ?

What is the forecast for month 8 ?

b. Compute MSE using the average of all data available as the forecast for the next period.

Mean squared error is ?

What is the forecast for month 8 ?

Answer 1

Given data :

Week	1	2	3	4	5	6
Value	18	14	16	12	17	14

Computing forecast and forecast accuracy using naive method :

Week	Value (Yi)	Forecast	Forecast Error (ei)	Absolute value of forecast error |ei|	Squared forecast error ei2	Percentage error	Absolute value of Percentage error
1	18	-	-	-	-	-	-
2	14	18	-4	4	16	-28.57	28.57
3	16	14	2	2	4	12.50	12.50
4	12	16	-4	4	16	-33.33	33.33
5	17	12	5	5	25	29.41	29.41
6	14	17	-3	3	9	-21.43	21.43
Total			-4	22	70	-41.42	125.24

a)  Mean absolute error is :

By definition

b)  Mean squared error is

By definition  

c) Mean absolute percentage error is :

By definition

  

d)  The forecast for week 7 is 14 using the naive method.