Consider the quarterly production data (in thousands of units) for the XYZ manufacturing company below. The normalized (adjusted) seasonal factors are winter = .9982, spring = .9263, summer = 1.139, and fall = .9365.
Based on the following deseasonalized observations (d_t), a trend line was estimated.
1998
1999
2000
The following Minitab output gives the straight-line trend equation fitted to the deseasonalized observations. Based on the trend equation given below, calculate the trend value for each period in the time series.
The regression equation is Deseasonalized = 10.1 + 1.91 × Time

Question

Consider the quarterly production data (in thousands of units) for the XYZ manufacturing company below. The normalized (adjusted) seasonal factors are winter = .9982, spring = .9263, summer = 1.139, and fall = .9365.

Based on the following deseasonalized observations (d_t), a trend line was estimated.
1998

1999

2000

The following Minitab output gives the straight-line trend equation fitted to the deseasonalized observations. Based on the trend equation given below, calculate the trend value for each period in the time series.
The regression equation is Deseasonalized = 10.1 + 1.91 × Time

Quizplus · Accepted Answer

The Answer of Consider the quarterly production data (in thousands of units) for the XYZ manufacturing company below. The normalized (adjusted) seasonal factors are winter = .9982, spring = .9263, summer = 1.139, and fall = .9365. Based on the following deseasonalized observations (d_t), a trend line was estimated. 1998 1999 2000 The following Minitab output gives the straight-line trend equation fitted to the deseasonalized observations. Based on the trend equation given below, calculate the trend value for each period in the time series. The regression equation is Deseasonalized = 10.1 + 1.91 × Time

Consider the Quarterly Production Data (In Thousands of Units) for the XYZ