|University of Phoenix | |Memo

      To: Steven Cooke

      From: Dana Drake

      Date: October 30, 2010

      Re: [pic]Applying Time Series Methodologies Simulation

      Intro

      This simulation was performed in order to see how time series methodologies can be used to help managers make accurate forecasts for their businesses. In this simulation, Blues Inc needs a Market Analyst to provide forecasts for their budget and sales. I used the linear regression and time series methodologies in an attempt to provide accurate forecasts their sales and budget.

                Week One

      In the first week I had to predict the average budget. I used the regression equation to set the budget and selected the competitor’s advertised budget as the independent variable. I should have selected sales as a variable for the regression analysis because it has a higher correlation coefficient than the competition’s budget. The optimal decision would have been to use sales as a variable for predicting the budget.

                Week Two

      For week two, I used the simple moving average model, but should have used the 2-period weighted moving average with a weight of 0.9 for the most recent observation. So my decisions were ok but not optimal.

              Week Three

      In Week three, I was asked to generate a quarterly forecast. The safety stock requirements were 10%. The simulation team saw my decisions as good. I used the centered moving average model and selected a data range of six years.

                Conclusion

      In the beginning of this simulation, the creator stated, “Statistics provides forecasting tools such as linear regression to help mangers make reasonably accurate forecasts”. (Simulation, pg 1). It is very important to be able to predict the relationships between variables such as sales and advertising budget. In this simulation, I used linear regression to predict... [continues]

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