Projected Total Sales of Sundance Direct Sales Calamba Branch in 2011 | A Term Paper for MGT 121 | Sandy Rose C. Nombrefia | Projected Total Sales of Sundance Direct Sales Calamba Branch in 2011 Introduction Billboards‚ signage and eye-catching advertisement paraphernalia of different direct selling companies are sprouting everywhere‚ either local or international. Many companies established names and compete to prolong their standing in the business world. Defined in businessdictionary
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research model is based on the assumption that Select one: there is a relationship between the time series and the dependent variable the independent variable is related to the dependent variable the variable being forecast is related to other variables in the environment there is a relationship between the time series and the independent variable e) the information is contained in a time series of data Which forecasting method is particularly good for determining customer preferences? Select
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barometers and thermometers for weather forecasters. In an attempt to forecast its future needs for mercury‚ Accuweather’s chief economist estimated average monthly mercury needs as: N = 500 + 10X where N = monthly mercury needs (units) and X = time period in months (January 2008= 0). The following monthly seasonal adjustment factors have been estimated using data from the past five years: Month Adjustment Factor January 15% April 10% July 20% September 5% December 10% (a) Forecast
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61% 4.63% 5.77 24.64% ARIMA(1‚0‚0)(2‚0‚0) 7.23% 5.11 8.51% 8.02% 6.56 28.01% *Mean of NHS for the historical period is 60.08 and for the holdout period is 23.42 The best model should be the one with the smallest error. Among these three time-series models‚ the decomposition with exponential smoothing trend has the smallest MAPE and RMSE for both historical period and holdout period. Therefore‚ we use this model and the data from January 2001 to October 2011 to perform the ex-ante point and
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Nicole-line breaks mean new slide important questions Forecasts are needed to predict demand all different teams within the company need the forecast different users have different time requirements and detail reqts you might have to collect more data if you don’t have enough cost depends on the scope of the project need to engage the users‚ so have to provide a feedback system The top chart appears to be a ore difficult to forecast but they just narrowed the y axiz 2nd chart down
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A Study on the Forecasted Sales of San Miguel Corporation for the year 2012 Redilyn Magbitang Ruth Anne Panganiban Lady Fatima Sandoval INTRODUCTION Background of the study San Miguel Corporation is the Philippines’ largest beverage‚ food and packaging company. The company now has more than 100 facilities around the Philippines and outside the country specifically Southeast Asia and China. One of the country’s premier business conglomerates‚ San Miguel’s extensive
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PowerPoint Slides Prepared by Robert F. Brooker‚ Ph.D. Copyright 2007 by Oxford University Press‚ Inc. Slide 2 PowerPoint Slides Prepared by Robert F. Brooker‚ Ph.D. Copyright 2007 by Oxford University Press‚ Inc. Slide 3 Time-Series Analysis • Secular Trend – Long-Run Increase or Decrease in Data • Cyclical Fluctuations – Long-Run Cycles of Expansion and Contraction • Seasonal Variation – Regularly Occurring Fluctuations • Irregular or Random Influences PowerPoint
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Total Revenues | 20X1 | $15‚000‚000 | 20X2 | $14‚250‚000 | 20X3 | $14‚000‚000 | 20X4 | $13‚500‚000 | Forecasting the total revenues for fiscal year 20X5 I will use the moving averages‚ weighted moving averages‚ exponential smoothing‚ and time series regression. Moving Averages Fiscal Year | Total Revenues
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exponential smoothing‚ and time series regression. For moving averages and weighted moving averages‚ use only the data for the past three fiscal years. For weighted moving averages‚ assign a value of 1 to the data for 20 X 2‚ a value of 2 to the data for 20 X 3‚ and a value of 3 to the data for 20 X 4. For exponential smoothing‚ assume that the last forecast for fiscal year 20 X 4 was $6‚300‚000. You decide on the alpha to be used for exponential smoothing. For time series regression‚ use the data
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Excel Problems 1. The following time series represent the total population of the United States‚ in thousands‚ over the last 12 years. |Year |Population (in 000‚s) | |1991 |253‚493 | |1992 |256‚894 | |1993 |260‚255 | |1994 |263‚436 | |1995 |266‚557 | |1996 |269‚667 | |1997 |272‚912
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