Question
In: Statistics and Probability
Consider the following gasoline time series data. Click on the datafile logo to reference the data....
Consider the following gasoline time series data. Click on the datafile logo to reference the data. show the exponential smoothing forecasts using = 0.1. Applying the MSE measure of forecast accuracy, would you prefer a smoothing constant of = .1 or = .2 for the gasoline sales time series (to 2 decimals)? MSE for = .1 9.25 MSE for = .2 8.98 Are the results the same if you apply MAE as the measure of accuracy (to 2 decimals)? MAE for = .1 2.57 MAE for = .2 2.57 What are the results if MAPE is used (to 2 decimals)? MAPE for = .1 12.95 % MAPE for = .2 12.95 % I am getting values mixed up for MAE and MAPE for the data set. Please help.
Solutions
orchestra answered 2 years agoRelated Solutions
Consider the following gasoline sales time series data. Click on the datafile logo to reference the...
Consider the following gasoline sales time series data. Click on
the datafile logo to reference the data.
Week
Sales (1000s of gallons)
1
16
2
22
3
18
4
23
5
18
6
16
7
20
8
17
9
22
10
20
11
16
12
22
a. Using a weight of 1/2 for the most recent
observation, 1/3 for the second most recent observation, and 1/6
third the...
Consider the following gasoline sales time series data. Click on the datafile logo to reference the...
Consider the following gasoline sales time series data. Click on
the datafile logo to reference the data.
Week
Sales (1000s of gallons)
1
16
2
21
3
19
4
24
5
18
6
16
7
19
8
17
9
23
10
20
11
15
12
22
a. Using a weight of 1/2 for the most recent
observation, 1/3 for the second most recent observation, and 1/6
third the...
Consider the following gasoline sales time series data. Click on the datafile logo to reference the...
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
21
3
19
4
24
5
18
6
15
7
21
8
19
9
22
10
19
11
15
12
23
a. Using a weight of 1/2 for the most recent
observation,1/3 for the second most recent observation, and 1/6
third the most...
Refer to the gasoline sales time series data in the given table. Click on the datafile...
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.
If required, round your answers to two decimal places.
Week
Sales
4 PeriodMoving Average
5 periodMoving Average...
Consider the following time series data.
Consider the following time series data. Week123456Value181516131716a. Choose the correct time series plot.What type of pattern exists in the data? b. Develop a three-week moving average for this time series. Compute MSE and a forecast for week 7. Round your answers to two decimal places. WeekTime Series ValueForecast118215316413517616 MSE: The forecast for week 7: c. Use α = 0.2 to compute the exponential smoothing values for the time series. Compute MSE and a forecast for week 7. Round your answers to two decimal places. WeekTime Series ValueForecast118215316413517616MSE: The...
Consider the following time series data.
Consider the following time series data.
Quarter
Year 1
Year 2
Year 3
1
5
8
10
2
2
4
8
3
1
4
6
4
3
6
8
(b)
Use a multiple regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data. Qtr1 = 1 if Quarter 1, 0 otherwise; Qtr2 = 1 if Quarter 2, 0 otherwise; Qtr3 = 1 if Quarter 3, 0 otherwise.
If required,...
Refer to the gasoline sales time series data in the given table.
Refer to the gasoline sales time series data in the given table.
Week
Sales (1000s of gallons)
1
17
2
21
3
19
4
24
5
19
6
15
7
21
8
19
9
23
10
19
11
15
12
22
Compute four-week and five-week moving averages for the time series. Round your answers to two decimal places.
Week
Sales
4-WeekMoving Average
5-WeekMoving Average
1
17
2
21
3
19
4
24
...
Refer to the gasoline sales time series data in the given table.
Refer to the gasoline sales time series data in the given table. a. Compute four-week and five-week moving averages for the time series. Round your answers to two decimal places.b. Compute the MSE for the four-week and five-week moving average forecasts. Round your intermediate calculations and final 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...
Refer to the gasoline sales time series data in Table below to answer the following (Copy...
Refer to the gasoline sales time series data in Table below to
answer the following (Copy the file to Excel when done submit
here)
1. Compute two- week , three-week and four-week moving averages
for the time series.
2. Compute the MSE for the two- week, three-week and four-week
moving average forecasts. (Look over the powerpoint)
3. Create a new column to show the trend line( y= mx+b) for the
table below
4. What appears to be the best number...
Refer to the gasoline sales time series data in Table below to answer the following (Copy...
Refer to the gasoline
sales time series data in Table below to answer the following (Copy
the file to Excel when done submit here)
1. Compute Three- week
and five-week moving averages for the time series.
2. Compute the MSE for
Three- week and five-week moving average forecasts.
3. What appears to be
the best number of weeks of past data (three or five) to use in the
moving average computation?
Week
Sale (1000s of
Gallons)
three-week
five-week
1
17...
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