Question

Consider the following time series.

Quarter | Year 1 | Year 2 | Year 3 |
---|---|---|---|

1 | 71 | 68 | 62 |

2 | 50 | 42 | 52 |

3 | 59 | 61 | 54 |

4 | 78 | 81 | 72 |

(a)

Construct a time series plot.

What type of pattern exists in the data?

The time series plot shows a horizontal pattern, but there is also a seasonal pattern in the data.

The time series plot shows a trend pattern, but there is also a seasonal pattern in the data.

The time series plot shows a horizontal pattern with no seasonal pattern present.

The time series plot shows a trend pattern with no seasonal pattern present.

(b)

Use the following dummy variables to develop an estimated regression equation to account for seasonal effects in the data:

*x*_{1} = 1 if quarter 1, 0 otherwise;
*x*_{2} = 1 if quarter 2, 0 otherwise;
*x*_{3} = 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=

Answer #1

a)

**The time series plot shows a horizontal pattern, but
there is also a seasonal pattern in the data.**

b)

Applying multiple regression on above data from excel: data-data analysis: regression: |

**y^ =77-10x1-29x2-19x3**

c)

forecast for 1st qtr of next year = |
67 |
||

forecast for 2nd qtr of next year = |
48 |
||

forecast for 3rd qtr of next year = |
58 |
||

forecast for 4th qtr of next year = |
77 |

Consider the following time series.
Quarter
Year 1
Year 2
Year 3
1
71
68
62
2
48
40
50
3
59
61
54
4
78
81
72
(a) Construct a time series plot.
What type of pattern exists in the data?
a)The time series plot shows a horizontal pattern, but there is
also a seasonal pattern in the data.
b)The time series plot shows a horizontal pattern with no
seasonal pattern present.
c)The time series plot shows a trend...

Consider the following time series.
Quarter
Year 1
Year 2
Year 3
1
71
68
62
2
49
41
51
3
57
59
52
4
78
81
72
(a) 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.
= _____?______
(b) Compute the quarterly forecasts for...

Consider the following time series data (Insert the data in an
Excel file):
Quarter Year 1 Year 2 Year 3
1 8 9 12
2 5 6 9
3 7 8 10
4 8 11 11
2.1. Construct a time series plot. What type of pattern exists
in the data?
2.2. 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...

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
58
60
53
4
77
80
71
(a)
Construct a time series plot.
A time series plot contains a series of 12 points connected by
line segments.
The horizontal axis is labeled: Year/Quarter. There are 12 tick
marks on the horizontal axis which have been divided up into 3
groups of 4 tick marks....

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
7
2
0
2
6
3
5
8
10
4
5
8
10
(a)
Choose the correct time series plot.
(i)
(ii)
(iii)
(iv)
Plot (iii)- Select your answer -Plot (i)Plot (ii)Plot (iii)Plot
(iv)Item 1
What type of pattern exists in the data?
Positive trend pattern, no seasonality- Select your answer
-Positive trend pattern, no seasonalityHorizontal pattern, no
seasonalityNegative trend pattern, no seasonalityPositive trend...

Consider the following time series data.
Quarter
Year 1
Year 2
Year 3
1
4
6
7
2
2
3
6
3
3
5
6
4
5
7
8
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 answers...

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,
round your...

Consider the following time series data.
Month
1
2
3
4
5
6
7
Value
24
13
20
12
19
23
15
(a)
Construct a time series plot.
A time series plot contains a series of 7 points connected by
line segments. The horizontal axis ranges from 0 to 8 and is
labeled: Month. The vertical axis ranges from 0 to 30 and is
labeled: Time Series Value. The points are plotted from left to
right at regular increments of...

Consider the following quarterly time series.
Quarter
Year 1
Year 2
Year 3
1
923
1,112
1,243
2
1,056
1,156
1,301
3
1,124
1,124
1,254
4
992
1,078
1,198
Use a multiple regression model with dummy variables for
quarters 1, 2, and 3 and a time variable. What is your forecast for
year 4 quarter 1? Round your answer to one decimal place.

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