Consider the following time series data. Quarter Year 1 Year 2 Year 3 11 13 14 10 12 Time Series Value 1 16T 15 14- 13 12 11 10- 9 8+ 2 3 4 9 10 (a) Construct a time series plot. 12 1 2 3 4 Year 1 14 1 2 3 4 Year 2 Year/Quarter 13 13 15 1234 Year 3 16- 15 14+ 13- 12- 11 10 9- 8+ 1 2 3 4 Year 1 1 2 3 4 Year 2 Year/Quarter 1 2 3 4 Year 3 پیدا 8 1 2 3 4 1 2 3 4 1 2 3 4 Year 1 Year 2 Year/Quarter Year 3 161 15 14- 13 12 8+ www 1 2 3 4 1 2 3 4 1 2 3 4 Year 1 Year 2 Year 3 Year/Quarter

MATLAB: An Introduction with Applications
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Consider the following time series data.
Quarter Year 1
O
Time Series Value
16
15
14-
13
12
11
10
1
9-
8.
7
2
3
4
(a) Construct a time series plot.
11
9
10
12
1 2 3 4
Year 1
quarter 3 forecast
quarter 4 forecast
Year 2
13
10
12
12.7
10.7
11.7
13.7
14
Year 3
1 2 3 4
Year 2
Year/Quarter
X
14
13
13
X
X
X
x
15
1 2 3 4
Year 3
16
15
14
13
What type of pattern exists in the data?
The time series plot shows a horizontal pattern and no seasonal pattern in the data.
The time series plot shows a linear trend and a seasonal pattern in the data.
The time series plot shows a linear trend and no seasonal pattern in the data.
O The time series plot shows a horizontal pattern, but there is also a seasonal pattern in the data.
10
9
8
7
1 2 3 4
Year 1
(c) Compute the quarterly forecasts for next year. (Round your answers to one decimal place.)
quarter 1 forecast
quarter 2 forecast
1 2 3 4
Year 2
Year/Quarter
1 2 3 4
Year 3
16
15
14-
13
12
11-
10
9
8+
7
(b) Use the following dummy variables to develop an estimated regression equation to account for any seasonal and linear trend effects in the data. (Round your numerical values to two decimal places.)
x₁ = 1 if quarter 1, 0 otherwise; x₂ = 1 if quarter 2, 0 otherwise; x3 = 1 if quarter 3, 0 otherwise
13.671x₁3x2 - 2x3
1 2 3 4
Year 1
1 2 3 4
Year 2
Year/Quarter
1 2 3 4
Year 3
16
15-
14-
13-
12
11
10-
9.
8+
7
m
1 2 3 4
Year 2
Year/Quarter
↓
1 2 3 4
Year 1
L
1 2 3 4
Year 3
Ⓡ
Transcribed Image Text:Consider the following time series data. Quarter Year 1 O Time Series Value 16 15 14- 13 12 11 10 1 9- 8. 7 2 3 4 (a) Construct a time series plot. 11 9 10 12 1 2 3 4 Year 1 quarter 3 forecast quarter 4 forecast Year 2 13 10 12 12.7 10.7 11.7 13.7 14 Year 3 1 2 3 4 Year 2 Year/Quarter X 14 13 13 X X X x 15 1 2 3 4 Year 3 16 15 14 13 What type of pattern exists in the data? The time series plot shows a horizontal pattern and no seasonal pattern in the data. The time series plot shows a linear trend and a seasonal pattern in the data. The time series plot shows a linear trend and no seasonal pattern in the data. O The time series plot shows a horizontal pattern, but there is also a seasonal pattern in the data. 10 9 8 7 1 2 3 4 Year 1 (c) Compute the quarterly forecasts for next year. (Round your answers to one decimal place.) quarter 1 forecast quarter 2 forecast 1 2 3 4 Year 2 Year/Quarter 1 2 3 4 Year 3 16 15 14- 13 12 11- 10 9 8+ 7 (b) Use the following dummy variables to develop an estimated regression equation to account for any seasonal and linear trend effects in the data. (Round your numerical values to two decimal places.) x₁ = 1 if quarter 1, 0 otherwise; x₂ = 1 if quarter 2, 0 otherwise; x3 = 1 if quarter 3, 0 otherwise 13.671x₁3x2 - 2x3 1 2 3 4 Year 1 1 2 3 4 Year 2 Year/Quarter 1 2 3 4 Year 3 16 15- 14- 13- 12 11 10- 9. 8+ 7 m 1 2 3 4 Year 2 Year/Quarter ↓ 1 2 3 4 Year 1 L 1 2 3 4 Year 3 Ⓡ
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