| Week | Value | UMA | WMA | ES |
| 1 | 18 | 18 | ||
| 2 | 13 | 18.0 | ||
| 3 | 16 | 17.0 | ||
| 4 | 11 | 15.7 | 15.3 | 16.8 |
| 5 | 17 | 13.3 | 13.0 | 15.6 |
| 6 | 14 | 14.7 | 14.8 | 15.9 |
| 7 | 14 | 14.5 | 15.5 |
Above is the excel output for each of the forecasts
For Unweighted moving average we simply take average of the last three period value.
For weighted moving average we take the following:
Therefore the weights are 3/6 , 2/6, 1/6
Forecasts for period 7 using
Unweighted moving average = 14
Weighted moving average = 14.5
Exponential smoothing = 15.5
1. Given the following time series data, compute the forecast (for 7) using: • Unweighted Moving...
Check My Work (3 remaining Consider the following gasoline sales time series data. Click on the datafile logo to reference the data Week Sales (1000s of gallons) 20 18 17 19 21 12 a. Using a weight of for the most recent observation, for the second most recent observation, and third the most recent abaervation, compute a threa-week weightad moving avarage fos the time series (to 2 decimals). Enter nagative values as negative numbers Weighted Moving Average Forecast (Error Time-Series...
Consider the following gasoline sales time series data. Click on the datafile logo to reference the data. Week Sales (1000s of gallons) 1 17 2 20 3 19 4 23 5 18 6 16 7 19 8 18 9 23 10 19 11 15 12 22 a. Using a weight of for the most recent observation, for the second most recent observation, and third the most recent observation, compute a three-week...
Consider the following gasoline sales time series data. Click onthe datafile logo to reference the data. Week Sales (1000s of gallons) 17 21 17 15 20 18 21 21 16 21 6 10 12 a. Using a weight of for the most recent observation, for the second most recent observation, and the time series (to 2 decimals). Enter negative values as negative numbers. third the most recent observation, compute a three-week weighted moving average for Forecast Weighted Moving Average Forecast...
Consider the following gasoline sales time series data. Click on the datafile logo to reference the data 00s Week of gallons) 18 21 18 24 18 17 1S 17 21 10 11 16 21 12 a. Using a welight of for the most recent observation, for the second most recent observation, andthird the most recent observation, compute a three-week weighted moving averape for the time serles (to 2 declmals). Enter negative values as negative numbers. Weighted Moving Forecast (Error)2 Time-Series...
Consider the following time series data. Week 1 2 3 4 5 6 Value 19 11 16 1017 15 (a) Construct a time series plot. 20 20 20 18 16 14 12 10 c 14 12 12 0 23 4 5 67 0 23 4 5 67 Week Weck Week 20 18 0 1 2345 6 7 Week What type of pattern exists in the data? The data appear to follow a seasonal pattern. The data appear to follow a...
Please help
Consider the following time series data. Week 1 N 3 4 5 6 Value 19 11 13 10 14 12 (a) Construct a time series plot. 20 18 20 18 14 12 10 Week 3 4 Week D 20 18+ 16 Time Series Value Time Series Value 5 Week 0 Wook What type of pattem exists in the data? The data appear to follow a cyclical pattern. The data appear to follow a trend pattem. The data appear...
Problem 08-06 Algo (Moving Averages and Exponential
Smoothing)
Consider the following time series data:
Month
1
2
3
4
5
6
7
Value
23
13
21
13
19
21
17
(a) Choose the correct time series plot Month (iv) Month Select your answer What type of pattern exists in the data? Select your answer- (b) Develop a three-month moving average for this time series. Compute MSE and a forecast for month 8. If required, round your answers to two decimal...
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Consider the following time series dataa. Which of the following is a correct time series plot for this data?b. Develop the three-week moving average forecasts for this time series. Compute MSE and a forecast for week 7 (to 2 decimals if necessary) c. Use α = .2 to compute the exponential smoothing forecasts for the time series. Compute MSE and a forecast for week 7 ( 2 decimals). d. Compare the three-week moving average approach with the exponential smoothing approach using α-.2,...
Consider the following time series data.
Week
1
2
3
4
5
6
Value
17
13
15
11
15
13
(a)
Choose the correct time series plot.
(i)
(ii)
(iii)
(iv)
- Select your answer -Graph (i)Graph (ii)Graph (iii)Graph
(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.
If required, round your answers...