Consider the following time series data. Week 1 2 3 4 5 6 Value 18 12 15 10 18 14 Using the naive method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy. (a) mean absolute error MAE = (b) mean squared error MSE = (c) mean absolute percentage error (Round your answer to two decimal places.) MAPE = % (d) What is the forecast for week 7?

Answer:

(a) MAE = 5.20

(b) MSE = 10

(c) MAPE = 38.60%

(d) Forecast for week 7 = 14

Step-by-step explanation:

Note: See the attached excel for the calculations of the Error, Error^2, and Error %.

(a) mean absolute error

MAE = Total of absolute value of error / Number of observations considered = |Error| / 5 = 26 / 5 = 5.20

(b) mean squared error

MSE = Total of Error^2 / Number of observations considered = Error^2 / 5 = 150 / 5 = 10

(c) mean absolute percentage error (Round your answer to two decimal places.)

MAPE = Total of Error % / Number of observations considered = Error % / 5 = 193.02 / 5 = 38.60%

(d) What is the forecast for week 7?

Since the forecast is based on the naive method (most recent value), the forecast for week 7 is value for week 6. Therefore, we have:

Forecast for week 7 = 14

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