a) Compute seasonal indices for each quarter based on a CMA b) Deseasonalize the
ID: 3230418 • Letter: A
Question
a) Compute seasonal indices for each quarter based on a CMA
b) Deseasonalize the data and develop a trend line on the deseasonalized data
c) Use the trend line to forecast the sales for each quarter of year 4.
d) Use the seasonal indices to adjust the forecasts found in part c.
e) Run regression using deseasonalized sales and time to get trend to obtain the final forecasts for periods, 13, 14, 15, 16
Lend and Seasonality Year Quarter Year EOLecast ection EOLJeaL4 Trend Forecas Seasonal ndez Quarter Forecast Quarter Trend QuarterlyExplanation / Answer
Year Quarter Sales MA CMA Ratio Avg_Ratio SI DeS Time 1 1 110 0.926249156 118.7585427 1 1 2 135 0.996728378 135.4431187 2 1 3 140 121.5 122.75 1.140529532 1.207945937 115.8992267 3 1 4 101 124 122.125 0.827021494 0.869076529 116.2153121 4 2 1 120 120.25 122 0.983606557 0.913913831 0.926249156 129.5547739 5 2 2 120 123.75 124.75 0.961923848 0.983454446 0.996728378 120.3938833 6 2 3 154 125.75 123.875 1.243188698 1.191859115 1.207945937 127.4891494 7 2 4 109 122 122.75 0.887983707 0.857502601 0.869076529 125.4204853 8 3 1 105 123.5 124.375 0.844221106 0.926249156 113.3604272 9 3 2 126 125.25 125.375 1.004985045 0.996728378 126.4135774 10 3 3 161 125.5 1.207945937 133.2841107 11 3 4 110 0.869076529 126.571132 12 a) S.I Q1 0.926249156 Q2 0.996728378 Q3 1.207945937 Q4 0.869076529 b) Deseasonalized data is as mentioned above in the table. Trend line based on time as dependent variable is 121.3277+0.4214(Time) c) Q1 121.3277+0.4214(13) 126.8059 Q2 121.3277+0.4214(14) 127.2273 Q3 121.3277+0.4214(15) 127.6487 Q4 121.3277+0.4214(16) 128.0701 d) Q1 117.4538579 Q2 126.8110604 Q3 154.1927285 Q4 111.3027179
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