Making Decisions Based on Demand and Forecasting

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1. Report the demographic and independent variables that are relevant to complete a demand analysis providing a rationale for the selection of the variables. This paper is going to layout the demographics of Virginia Beach-Norfolk-Newport News Virginia and the independent variables i.e. price of pizza and food service manager annual wage in relation to relevant demand analysis for pizza in the past 14 years. 2. Using Excel or other calculation software, input the data you collected in criterion one to calculate an estimated regression. Then, from the calculation provided, interpret the coefficient of determination indicating how it will influence your decision to open the pizza business. Explain any additional variables that may improve the coefficient of determination. The independent variables used to analyze coefficient of determination here were the average income of food service manager and the average price of pizza in a time series regression analysis. Based on the data collect per the spreadsheet attached, the percent change of the sales is explained by R square percent of 95% change in price of pizza and income. There is positive coefficient between the independent variables and sales. This means as sales increase so does the average food service manager salaries increase by 0.0003 coefficient however price goes down by the 0.25 value. Per the data food service manager salaries are down by 8.9% from last year this time therefore to open a new pizza operation would be a good capitalize managerial decision at this time other cost factors remain the same. 3. Test the statistical significance of the variables and the regression equation indicating how it will impact your decision to open the pizza business. Per the data collected the independent variables price and wages are statistical significant of the dependent variable sales.

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