Answered step by step
Verified Expert Solution
Question
1 Approved Answer
Consider the following time series data: Month 1 2 3 4 5 6 7 Value 23 14 20 11 20 23 14 (a) Compute MSE
Consider the following time series data:
Month | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
Value | 23 | 14 | 20 | 11 | 20 | 23 | 14 |
(a) | Compute MSE using the most recent value as the forecast for the next period. |
If required, round your answer to one decimal place. | |
What is the forecast for month 8? | |
If required, round your answer to one decimal place. Do not round intermediate calculation. | |
(b) | Compute MSE using the average of all the data available as the forecast for the next period. |
If required, round your answer to one decimal place. Do not round intermediate calculation. | |
What is the forecast for month 8? | |
If required, round your answer to one decimal place. | |
(c) | Which method appears to provide the better forecast? |
- Select your answer - (i) Naive (ii) All data average |
Consider the following time series data.
Week | 1 | 2 | 3 | 4 | 5 | 6 |
Value | 18 | 13 | 16 | 11 | 17 | 14 |
(a) | Choose the correct time series plot. | |||||||||||||||||||||
| ||||||||||||||||||||||
- Select your answer -Plot (i)Plot (ii)Plot (iii)Plot (iv)Item 1 | ||||||||||||||||||||||
What type of pattern exists in the data? | ||||||||||||||||||||||
- Select your answer -Horizontal PatternTrend PatternItem 2 | ||||||||||||||||||||||
(b) | Develop a three-week moving average for this time series. Compute MSE and a forecast for week 7. | |||||||||||||||||||||
Do not round intermediate calculations. If required, round your answers to two decimal places. | ||||||||||||||||||||||
| ||||||||||||||||||||||
MSE: | ||||||||||||||||||||||
The forecast for week 7: | ||||||||||||||||||||||
(c) | Use= 0.2 to compute the exponential smoothing values for the time series. Compute MSE and a forecast for week 7. | |||||||||||||||||||||
Do not round intermediate calculations. If required, round your answers to two decimal places. | ||||||||||||||||||||||
| ||||||||||||||||||||||
MSE: | ||||||||||||||||||||||
The forecast for week 7: | ||||||||||||||||||||||
(d) | Compare the three-week moving average forecast with the exponential smoothing forecast using= 0.2. Which appears to provide the better forecast based on MSE? | |||||||||||||||||||||
- Select your answer -Three-week moving averageExponential SmoothingItem 15 | ||||||||||||||||||||||
Explain. | ||||||||||||||||||||||
Using this approach results in a - Select your answer -largersmallerItem 16 MSE. | ||||||||||||||||||||||
(e) | Use trial and error to find a value of the exponential smoothing coefficientthat yields the minimum MSE. Do not round intermediate calculations. Use a two-decimal digit precision for the exponential smoothing coefficient. | |||||||||||||||||||||
alpha: |
Refer to the gasoline sales time series data in the given table.
Click on the datafile logo to reference the data.
Week | Sales (1,000s of gallons) |
1 | 17 |
2 | 21 |
3 | 19 |
4 | 23 |
5 | 18 |
6 | 16 |
7 | 20 |
8 | 18 |
9 | 22 |
10 | 20 |
11 | 15 |
12 | 22 |
(a) | Compute four-week and five-week moving averages for the time series. | ||||||||||||||||||||||||||||||||||||||||||||||||||||
Do not round intermediate calculations. If required, round your answers to two decimal places. | |||||||||||||||||||||||||||||||||||||||||||||||||||||
| |||||||||||||||||||||||||||||||||||||||||||||||||||||
(b) | Compute the MSE for the four-week and five-week moving average forecasts. | ||||||||||||||||||||||||||||||||||||||||||||||||||||
Do not round intermediate calculations. If required, round your answers to two decimal places. | |||||||||||||||||||||||||||||||||||||||||||||||||||||
MSE for four-week moving average = | |||||||||||||||||||||||||||||||||||||||||||||||||||||
MSE for five-week moving average = | |||||||||||||||||||||||||||||||||||||||||||||||||||||
(c) | What appears to be the best number of weeks of past data (three, four, or five) to use in the moving average computation? Recall that the MSE for the three-week moving average is 10.22. | ||||||||||||||||||||||||||||||||||||||||||||||||||||
- Select your answer - Three Four Five |
Consider the following gasoline sales time series. If needed, round your answers to two-decimal digits.
Week | Sales (1,000s of gallons) |
1 | 17 |
2 | 23 |
3 | 14 |
4 | 25 |
5 | 17 |
6 | 16 |
7 | 22 |
8 | 19 |
9 | 21 |
10 | 19 |
11 | 17 |
12 | 23 |
(a) | Show the exponential smoothing forecasts using = 0.1, and = 0.2. | ||||||||
| |||||||||
(b) | Applying the MSE measure of forecast accuracy, would you prefer a smoothing constant of = 0.1 or = 0.2 for the gasoline sales time series? | ||||||||
An - Select your answer - = 0.1 = 0.2Item 3 smoothing constant provides the more accurate forecast, with an overall MSE of . | |||||||||
(c) | Are the results the same if you apply MAE as the measure of accuracy? | ||||||||
An - Select your answer - = 0.1 = 0.2Item 5 smoothing constant provides the more accurate forecast, with an overall MAE of . | |||||||||
(d) | What are the results if MAPE is used? | ||||||||
An - Select your answer - = 0.1 = 0.2Item 7 smoothing constant provides the more accurate forecast, with an overall MAPE of . |
Thanks
Step by Step Solution
There are 3 Steps involved in it
Step: 1
Get Instant Access to Expert-Tailored Solutions
See step-by-step solutions with expert insights and AI powered tools for academic success
Step: 2
Step: 3
Ace Your Homework with AI
Get the answers you need in no time with our AI-driven, step-by-step assistance
Get Started