Consider the following time series data: Week 1 2 3 4 5 6 Value 18 13 16 11 17 14 1)Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy. Mean absolute error Mean squared error Mean absolute percentage error What is the forecast for week 7?
Consider the following time series data:
Week 1 2 3 4 5 6
Value 18 13 16 11 17 14
1)Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy.
- Mean absolute error
- Mean squared error
- Mean absolute percentage error
- What is the forecast for week 7?
2) Refer to the time series data in Exercise 1. Using the average of all the historical data as a forecast for the next period. Compute the following measures of forecast accuracy
- Mean absolute error
- Mean squared error
- Mean absolute percentage error
- What is the forecast for week 7?
3) Exercise 1 and 2 used different forecasting methods. Which method appears to provide the more accurate forecast for the historical data? Explain.
4 Consider the following time series data.
Month 1 2 3 4 5 6 7
Value 24 13 20 12 19 23 15
- Compute MSE using the most recent value as the forecast for the next period. What is the forecast for month 8?
- Compute MSE using the average of all the date available as the forecast for the next period. What is the forecast for month 8?
- Which method appears to provide the better forecast?
5) Consider the following time series data:
Week 1 2 3 4 5 6
Value 18 13 16 11 17 14
- Construct a time series plot. What type of pattern exist in the data?
- Develop a three – week moving average for the time series. Compute MSE and a forecast cast for week 7.
- Use alpha = 0.2 to compute the exponential smoothing value for the time series. Compute MSE and a forecast for week 7.
- Compare the three -week moving average forecast with exponential smoothing forecast using alpha = 0.2. Which appears to provide the better forecast based on MSE? Explain
- Use trial and error to find a value of the exponential smoothing. Coefficient Alpha that result in a smaller MSE than what you calculated for alpha = 0.2.
6) 4 Consider the following time series data.
Month 1 2 3 4 5 6 7
Value 24 13 20 12 19 23 15
- Construct a time series plot. What type of pattern exist in the data?
- Develop a three – week moving average for the time series. Compute MSE and a forecast cast for week 8.
- Use alpha = 0.2 to compute the exponential smoothing value for the time series. Compute MSE and a forecast for week 8.
- Compare the three -week moving average forecast with exponential smoothing forecast using alpha = 0.2. Which appears to provide the better forecast based on MSE? Explain
- Use trial and error to find a value of the exponential smoothing. Coefficient Alpha that result in a smaller MSE than what you calculated for alpha = 0.2.
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