Question
In: Statistics and Probability
A statistical program is recommended. Consider the following time series. Quarter Year 1 Year 2 Year...
A statistical program is recommended.
Consider the following time series.
| Quarter | Year 1 | Year 2 | Year 3 |
|---|---|---|---|
| 1 | 72 | 69 | 63 |
| 2 | 49 | 41 | 51 |
| 3 | 59 | 61 | 54 |
| 4 | 77 | 80 | 71 |
Use the following dummy variables to develop an estimated regression equation to account for seasonal effects in the data:
x1 = 1 if quarter 1, 0 otherwise; x2 = 1 if quarter 2, 0 otherwise; x3 = 1 if quarter 3, 0 otherwise.
=
(c) Compute the quarterly forecasts for next year.
quarter 1 forecast
quarter 2 forecast
quarter 3 forecast
quarter 4 forecast
Solutions
orchestra answered 2 years agoRelated Solutions
Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 2 4...
Consider the following time series data.
Quarter
Year 1
Year 2
Year 3
1
2
4
5
2
4
5
8
3
1
3
4
4
7
9
10
(a)
Choose the correct time series plot.
(i)
(ii)
(iii)
(iv)
- Select your answer -Plot (i)Plot (ii)Plot (iii)Plot (iv)Item
1
What type of pattern exists in the data?
- Select your answer -Positive trend pattern, no
seasonalityHorizontal pattern, no seasonalityNegative trend
pattern, no seasonalityPositive trend pattern, with
seasonalityHorizontal pattern, with...
Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 2 5...
Consider the following time series data.
Quarter
Year 1
Year 2
Year 3
1
2
5
7
2
0
2
6
3
5
8
10
4
5
8
10
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, round your...
Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 2 5...
Consider the following time series data.
Quarter
Year 1
Year 2
Year 3
1
2
5
7
2
0
2
6
3
5
8
10
4
5
8
10
(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, round your...
Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 2 3...
Consider the following time series data.
Quarter
Year 1
Year 2
Year 3
1
2
3
4
4
2
3
5
6
3
5
7
7
6
6
8
Graph this data series (use the X-Y scatter/chart tool in Excel
for this plot). What type of pattern(s) exists in the data? Does
the graph suggest that these data exhibit seasonality? What is the
length of the season in this particular case?
Determine the seasonal factors for each quarter using
METHOD...
Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 2 3...
Consider the following time series data.
Quarter
Year 1
Year 2
Year 3
1
2
3
4
4
2
3
5
6
3
5
7
7
6
6
8
Graph this data series (use the X-Y scatter/chart tool in Excel
for this plot). What type of pattern(s) exists in the data? Does
the graph suggest that these data exhibit seasonality? What is the
length of the season in this particular case?
Determine the seasonal factors for each quarter using
METHOD...
Consider the following time series. Quarter Year 1 Year 2 Year 3 1 71 68 62...
Consider the following time series.
Quarter
Year 1
Year 2
Year 3
1
71
68
62
2
49
41
51
3
58
60
53
4
83
85
72
b. Use the following dummy variables to develop
an estimated regression 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. Enter negative
values as negative numbers.
Value =...
Consider the following time series: Quarter Year 1 Year 2 Year 3 1 74 71 65...
Consider the following time series:
Quarter
Year 1
Year 2
Year 3
1
74
71
65
2
44
36
46
3
61
63
56
4
78
81
72
Use a multiple linear 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. For
subtractive or negative numbers...
Consider the following time series. Quarter Year 1 Year 2 Year 3 1 70 67 61...
Consider the following time series.
Quarter
Year 1
Year 2
Year 3
1
70
67
61
2
48
40
50
3
58
60
53
4
79
82
73
(b)Use the following dummy variables to develop an estimated
regression equation to account for seasonal effects in the
data:
x1 = 1 if quarter 1, 0 otherwise;
x2 = 1 if quarter 2, 0 otherwise;
x3 = 1 if quarter 3, 0 otherwise.
=
(c)Compute the quarterly forecasts for next year.
quarter...
Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 5 8...
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
A.) 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,
round your...
Consider the following time series: Quarter Year 1 Year 2 Year 3 1 66 63 57...
Consider the following time series:
Quarter
Year 1
Year 2
Year 3
1
66
63
57
2
48
40
50
3
59
61
54
4
73
76
67
Use a multiple linear 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. For
subtractive or negative numbers...
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