Problems 1 and 2 used different forecasting methods. Which method appears to provide the more accurate forecasts for the historical data? Explain. Consider the following time series data: Week 1 2 3 4 5 6 Value 18 13 16 11 17 14 Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy: a. Mean absolute error b. Mean squared error c. Mean absolute percentage error d. What is the forecast for week 7? 2. Refer to the time series data in Problem 1. Using the average of all the historical data as a forecast for the next period, compute the following measures of forecast accuracy: a. Mean absolute error b. Mean squared error c. Mean absolute percentage error d. What is the forecast for week 7?
Problems 1 and 2 used different forecasting methods. Which method appears to provide the more accurate forecasts for the historical data? Explain.
- Consider the following time series data:
Week |
1 |
2 |
3 |
4 |
5 |
6 |
Value |
18 |
13 |
16 |
11 |
17 |
14 |
Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy:
a.
b. Mean squared error
c. Mean absolute percentage error
d. What is the forecast for week 7?
2. Refer to the time series data in Problem 1. Using the average of all the historical data as a forecast for the next period, compute the following measures of forecast accuracy:
a. Mean absolute error
b. Mean squared error
c. Mean absolute percentage error
d. What is the forecast for week 7?
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