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. The linear regression trend equation is tr_t = 10.1 + 1.91t.
Use the forecasting equation _t = tr₁ × sn_t and calculate the forecasted demand for the fall quarter of 1998 and summer quarter of 2000.

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. The linear regression trend equation is tr_t = 10.1 + 1.91t.
Use the forecasting equation

_t = tr₁ × sn_t and calculate the forecasted demand for the fall quarter of 1998 and summer quarter of 2000.

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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. The linear regression trend equation is tr_t = 10.1 + 1.91t. Use the forecasting equation _t = tr₁ × sn_t and calculate the forecasted demand for the fall quarter of 1998 and summer quarter of 2000.

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