Question
In: Statistics and Probability
Problem 15-01 (Algorithmic) Consider the following time series data. Week 1 2 3 4 5 6...
Problem 15-01 (Algorithmic)
Consider the following time series data.
| Week | 1 | 2 | 3 | 4 | 5 | 6 |
| Value | 19 | 13 | 15 | 10 | 18 | 14 |
Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy.
- Mean absolute error. Round your answer to one decimal
place.
- Mean squared error. Round your answer to one decimal
place.
- Mean absolute percentage error. Round your answer to two
decimal places.
- What is the forecast for week 7? Round your answer to the nearest whole number.
Solutions
orchestra answered 1 year agoRelated Solutions
Problem 6-01 (Algorithmic) Consider the following time series data. Week 1 2 3 4 5 6...
Problem 6-01 (Algorithmic)
Consider the following time series data.
Week
1
2
3
4
5
6
Value
18
12
16
10
19
13
Using the naïve method (most recent value) as the forecast for
the next week, compute the following measures of forecast
accuracy.
Mean absolute error. If required, round your answer to one
decimal place.
Mean squared error. If required, round your answer to one
decimal place.
Mean absolute percentage error. If required, round your
intermediate calculations and final...
Problem 15-03 (Algorithmic) Consider the following time series data. Week 1 2 3 4 5 6...
Problem 15-03 (Algorithmic) Consider the following time series
data.
Week 1 2 3 4 5 6
Value 20 13 15 11 18 13
Using the naïve method (most recent value) as the forecast for
the next week, compute the following measures of forecast accuracy:
Mean absolute error (MAE) Mean squared error (MSE) Mean absolute
percentage error (MAPE) Round your answers to two decimal
places.
MAE =
MSE =
MAPE =
Using the average of all the historical data as a...
Problem 15-03 (Algorithmic) Consider the following time series data. Week 1 2 3 4 5 6...
Problem 15-03 (Algorithmic)
Consider the following time series data.
Week 1 2 3 4 5 6
Value 19 14 15 11 19 15
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 (MAE)
b. Mean squared error (MSE)
c. Mean absolute percentage error (MAPE)
Round your answers to two decimal places.
MAE =
MSE =
MAPE =
Using the average of all the historical...
Problem 15-05 (Algorithmic) Consider the following time series data. Week 1 2 3 4 5 6...
Problem 15-05 (Algorithmic)
Consider the following time series data.
Week
1
2
3
4
5
6
Value
16
13
18
11
15
14
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.
Week
Time Series
Value
Forecast
1
16
2
13
3
18
4
11
5
15
6
14
MSE: ——————
The forecast for week 7: ————————
Use = 0.2 to compute the exponential smoothing
values...
Problem 15-05 (Algorithmic) Consider the following time series data. Week 1 2 3 4 5 6...
Problem 15-05 (Algorithmic)
Consider the following time series data.
Week
1
2
3
4
5
6
Value
16
13
18
11
15
14
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.
Week
Time Series
Value
Forecast
1
16
2
13
3
18
4
11
5
15
6
14
MSE:
The forecast for week 7:
Use = 0.2 to compute the exponential smoothing
values for the...
Question 1. Consider the following time series data. Week 1 2 3 4 5 6 Value...
Question 1. Consider the following time series
data.
Week
1
2
3
4
5
6
Value
118
113
116
111
117
114
Construct a time series plot. What type of pattern
exists in the data?
Develop a three-week moving average for this time
series. Compute MSE and a forecast for week 7.
Use a =0.2 to compute the exponential smoothing values
for the time series. Compute MSE and a forecast for week
7.
Compare the three-week moving average forecast with...
Consider the following time series data. Week 1 2 3 4 5 6 Value 19 12...
Consider the following time series data.
Week
1
2
3
4
5
6
Value
19
12
15
11
18
13
a. Use α = 0.2 to compute the exponential smoothing
forecasts for the time series.
Week
Time Series
Value
Forecast
1
19
2
12
3
15
4
11
5
18
6
13
Compute MSE. (Round your answer to two decimal places.)
MSE =
b. Use a smoothing constant of α = 0.4 to compute the
exponential smoothing forecasts.
Week
Time...
Consider the following time series data. Week 1 2 3 4 5 6 Value 18 13...
Consider the following time series data.
Week
1
2
3
4
5
6
Value
18
13
16
11
17
14
a. Use a smoothing constant of a = 0.4 to
compute the MSE (to 2 decimals).
(___)
2.Consider the following time series data.
Week
1
2
3
4
5
6
Value
19
13
17
12
17
15
b. Develop the three-week moving average
forecasts for this time series. Compute MSE and a forecast for week
7 (to 2 decimals if...
Consider the following time series data. Week 1 2 3 4 5 6 Value 18 12...
Consider the following time series data.
Week
1
2
3
4
5
6
Value
18
12
16
10
17
15
(a) Construct a time series plot.
What type of pattern exists in the data? The data appear to
follow a horizontal pattern.
(b) Develop the three-week moving average forecasts for this
time series. (Round your answers to two decimal places.)
Week
Time Series
Value
Forecast
1
18
2
12
3
16
4
10
15.33
5
17
12.67
6
15
14.33...
Consider the following time series data. Week 1 2 3 4 5 6 Value 20 13...
Consider the following time series data.
Week
1
2
3
4
5
6
Value
20
13
15
10
18
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
If required, round your answer to one decimal place.
(b)
Mean squared error
If required, round your answer to one decimal place.
(c)
Mean absolute percentage error
If required, round your intermediate calculations and final...
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