Trend Analysis with Seasonality
The following data is retail sales for the ABC Company.
|
Period |
1997 |
1998 |
1999 |
|
Jan. |
98.8 |
105.6 |
106.4 |
|
Feb. |
95.6 |
99.7 |
105.8 |
|
Mar. |
110.2 |
114.2 |
120.4 |
|
Apr. |
113.1 |
115.7 |
125.4 |
|
May |
120.3 |
125.4 |
129.1 |
|
Jun. |
115.0 |
120.4 |
129.0 |
|
Jul. |
115.5 |
120.7 |
129.3 |
|
Aug. |
121.1 |
124.1 |
131.5 |
|
Sept. |
113.8 |
124.4 |
124.5 |
|
Oct. |
115.8 |
123.8 |
128.3 |
|
Nov. |
118.1 |
121.4 |
126.9 |
|
Dec. |
138.6 |
152.1 |
157.2 |
a. Compute a regression line for the data to predict sales by month for the year 2000.
b. Calculate monthly seasonal indices for each month.
c. Compute a seasonally adjusted forecast for each month in 2000.
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