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An equation is made from a scatterplot of deseasonalised data. Use this equation to
predict the sales in the first quatre of 2007. Because the questions wants us
to predict the sales in the first quatre of 2007, it is implying the actual raw sales... NOT DESEASONALISE VALUES. This means you have to find the deasonalised figure by using the equation, and then convert this fiqure to its raw value by multiplying the deseasonalised figure by its corresponding seasonal index For example... (TSM 2007 1)
From a scatterplot of deseasonalised data of sales (in thousands of dollars) in 2006 a least
squares regression line is fitted. It is found to have the equation y = −1.4t + 22.8 . Some of the
seasonal indices for 2006 are given in the table.
Seasonal Index Q1 = 0.72 Q2 = 1.68
Assuming t = 1 is Quarter 1 of 2006,
a prediction of the sales in the first quarter of 2007 using
this information is closest to
y = −1.4 X 5 + 22.8
= 15.8 X Seasonal index (Q1)
= 15.8 X .72
= 11.367
= C
A. $11.38
B. $15.80
C. $11376
D. $15800
E. $21944
Conversely, if the qustion had said predict the deseasonalised sales in the first quatre of 2007, Then you wouldn't have to convert the deasonalised value to raw data.
Make sure you make this distinguishment. Back to studying