Question
In: Operations Management
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 1 (multiplicative seasonal model).
- Compute the quarterly forecasts for next year (Year 4)?
Solutions
Expert Solution
As you can see in the table first calculate the total for perticular year. Then calculate the average from the total. Now devide the quaterly value by average and find the seasonal factor for perticular year. Repeat this for all years and quarters Then find the average seasonal factor for quarter 1 for all the years. Then repeat this for all the quarters.
As we forecasted earlier that 4th year demand would be 35. Then aveage demand per quarter would be 8.75 Now multiply this average with average seasonal factor of perticular quarter and get the forcast of 4th year.
keosha answered 1 month agoRelated Solutions
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 3 6...
Consider the following time series data.
Quarter
Year 1
Year 2
Year 3
1
3
6
7
2
4
1
8
3
1
7
5
4
5
7
8
a. Which of the following is a time series
plot?
- Select your answer -time series plot #1time series plot #2time
series plot #3Item 1
What type of pattern exists in the data?
- Select your answer -upward linear trendnonlinear trend and a
seasonal patternlinear trend and a seasonal patternslight
curvaturedownward...
Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 3 6...
Consider the following time series data.
Quarter
Year 1
Year 2
Year 3
1
3
6
8
2
2
4
8
3
4
7
9
4
6
9
11
.
(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 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 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 data. Quarter Year 1 Year 2 Year 3 1 4 6...
Consider the following time series data.
Quarter
Year 1
Year 2
Year 3
1
4
6
7
2
0
1
4
3
3
5
6
4
5
7
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. 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
1
3
7
3
3
6
8
4
7
10
12
(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 4 6...
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
Compute seasonal indexes and adjusted seasonal indexes for the
four quarters (to 3 decimals).
Quarter
Seasonal
Index
Adjusted
Seasonal
Index
1
(___)
(___)
2
(___)
(___)
3
(___)
(___)
4
(___)
(___)
Total
(___)
Consider the following time series data.
Quarter
Year 1
Year 2
Year 3
1
5
5
6...
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