After plotting the above sales, the seasonal pattern was discovered besides the

Question

After plotting the above sales, the seasonal pattern was discovered besides the trend component. The following table ShoWS the deseasonalized demands e revised dada for linear regression model (3) (5) XX yd ACTUAL DESEASONALizED PERIOD DEMAND AVERAGE OF THE SAME SEASONAL DEMAND (d) CoL (1)X COL, (3)- COL. (5) (COL. 19 QUARTER QUARTERS OF EACH YEAR COL. (6) ACTOR 7357 7357 600 600 t 2400 3800)/3 0,82 2,266.7 2,8247 1.550 1,550 3100 4500)/3 110 4124 3050 4,631.9 1,500 1,500 2,600 4,000)/3 0,97 5440 2,700 1500 1,500 2900 4900/3 5,3790 112 1,344.8 3100 14,7132 2,400 0.82 2,942.6 16,948.4 2,8247 110 3100 187336 2,600 0,97 2.6762 2,5999 20,798.9 112 64 2900 41932.7 082 4,6592 3800 41,004.1 4100.4 110 4,500 00 121 45,2901 0,97 41173 4,000 52,714.5 44 4,3929 4900 112 650 2657069 33,350 1203 33.3501

Explanation / Answer

Step 1: Find XY and X2 as it was done in the table below.

Step 2: Find the sum of every column:

X=78 , Y=33368.1 , XY=265725.4 , X2=650

Step 3: Use the following equations to find a and b (a is the y-intercept and b is the slope of the regression line)

:

We find a = 561.005

and

b = 341.488

Projection for x =15 is 341.488*15+ 561.005= 5683.325

Projection for x =20 is 7390.765

Comment on the (small) numerical differences: Most probably due to round off errors.

In each problem , take the nearest choice.

.

X Y XY XX 1 753.7 753.7 1 2 1412.4 2824.8 4 3 1544 4632 9 4 1344.8 5379.2 16 5 2942.6 14713 25 6 2824.7 16948.2 36 7 2676.2 18733.4 49 8 2599.9 20799.2 64 9 4659.2 41932.8 81 10 4100.4 41004 100 11 4117.3 45290.3 121 12 4392.9 52714.8 144

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