The following table gives monthly data for four years in million tons of consumption of ice...
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The following table gives monthly data for four years in million tons of consumption of ice cream in a country. Plot the series and comment on the visible seasonality and trend. Estimate the centered moving averages for this monthly series. Plot CMA and comment. Next, estimate the SI component which only includes seasonal and irregular movements of the series. Then find the seasonal indexes for the twelve months removing the irregular component. Find the de-seasonalized levels for the series. Plot De- seasonalized Y and comment. Then estimate the trend values for the four sample years and the 12 months of the year 2019 (beyond the sample years) using linear regression. Finally, make the forecast for the 12 months of 2015 using the Ratio-to-Moving Average method to capture the Trend and Seasonal patterns, using Excel. Plot the forecasted values for the 60 periods including 12 months of the year 2019. Plot the errors for in-sample periods and calculate RMSE. Comment on the error plot with respect to the existence of pattern or lack of visible pattern. Month/Year 2015 2016 2017 800 860 1110 810 870 1120 840 900 1160 1050 1230 1340 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 900 1000 1170 1100 1300 1450 1780 1160 1380 1530 1870 1100 1310 1450 1770 1050 1250 1390 1720 1010 1200 1350 1635 850 1400 830 1050 1020 1220 2018 1290 1330 1360 1470 1620 1170 1370 The following table gives monthly data for four years in million tons of consumption of ice cream in a country. Plot the series and comment on the visible seasonality and trend. Estimate the centered moving averages for this monthly series. Plot CMA and comment. Next, estimate the SI component which only includes seasonal and irregular movements of the series. Then find the seasonal indexes for the twelve months removing the irregular component. Find the de-seasonalized levels for the series. Plot De- seasonalized Y and comment. Then estimate the trend values for the four sample years and the 12 months of the year 2019 (beyond the sample years) using linear regression. Finally, make the forecast for the 12 months of 2015 using the Ratio-to-Moving Average method to capture the Trend and Seasonal patterns, using Excel. Plot the forecasted values for the 60 periods including 12 months of the year 2019. Plot the errors for in-sample periods and calculate RMSE. Comment on the error plot with respect to the existence of pattern or lack of visible pattern. Month/Year 2015 2016 2017 800 860 1110 810 870 1120 840 900 1160 1050 1230 1340 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 900 1000 1170 1100 1300 1450 1780 1160 1380 1530 1870 1100 1310 1450 1770 1050 1250 1390 1720 1010 1200 1350 1635 850 1400 830 1050 1020 1220 2018 1290 1330 1360 1470 1620 1170 1370
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Answer Trend and Seasonal Movement in Ice Cream Consumption The table given above shows monthly data for four years in million tons of consumption of ice cream for a country In order to better underst... View the full answer
Related Book For
Applied Regression Analysis and Other Multivariable Methods
ISBN: 978-1285051086
5th edition
Authors: David G. Kleinbaum, Lawrence L. Kupper, Azhar Nizam, Eli S. Rosenberg
Posted Date:
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