Managerial Economics and Globalization Eco 550

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Making Decisions Based on Demand and Forecasting
Week 3 Assignment

Managerial Economics and Globalization ECO 550

May 9, 2013

Making Decisions Based on Demand and Forecasting

Report the demographic and independent variables that are relevant to complete a demand analysis providing a rationale for the selection of the variables. As the Marketing and Public Relations Manager for my community, I am conducting research about the demographics of our community. My research will be based on demand and forecasting about the demographics of Darlington, SC. This research is the direct result of Domino Pizza’s’ interest in entering the marketplace in our community. Conducting this demand analysis and forecast for pizza will aid in the decision as to whether or not Domino’s should establish a presence in our community. There are many variables relevant to a company’s major business decisions and success. Independent variables or experimental variables as they are sometimes called is the variable being manipulated in the experiment to show the effect on the dependent variable. The dependent variable also known as the response variable is the variable being observed in the experiment. A change in the independent variable is what causes the change if any in the dependent variable, which is the purpose of the experiment. Marketing departments use demographic variables like income level, gender, location, race, and family size, as an important input when formulating target customer profiles. Research for the demographics in this report were taken from the 2012 United States Census Bureau for Darlington, South Carolina and include average yearly income, total population and number of people per household. The remaining variables for this report include pizza and soda costs. The data for this report is as follows; population: 68,139, number of people per household: 2.56, average income per household: $38,567, price large meat lovers pizza -feeds approx. 3-4 people: $12.10 after taxes, price per Sierra Mist 2L soda: $2.5, number of households: 26,279 (United States Cesu Bureau, 2012).

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. Test the statistical significance of the variables and the regression equation indicating how it will impact your decision to open the pizza business. SUMMARY OUTPUT| |

Regression Statistics| Column1|
Multiple R| 0.889|
R Square| 0.791|
Adjusted R Square| 0.582|
Standard Error| 1244.969|
Observations| 11|

ANOVA| | | | | |
Column1| df| SS| MS| F| Significance F|
Regression| 5| 29295711.280| 5859142.256| 3.780| 0.085| Residual| 5| 7749743.266| 1549948.653| | |
Total| 10| 37045454.545| | | |
RESIDUAL OUTPUT| | |
Observation| Predicted Demand| Residuals|
1| 339.293| 660.707|
2| 2612.545| -1112.545|
3| 1610.176| 389.824|
4| 2636.072| -136.072|
5| 3549.304| -549.304|
6| 5816.105| 1683.895|
7| 4644.584| -1144.584|
8| 4632.769| -632.769|
9| 3572.466| 927.534|
10| 5354.141| -354.141|
11| 5232.544| 267.456|

Column1| Coefficients| Standard Error| t Stat| P-value| Lower 95%| Upper 95%| Lower 95.0%| Upper 95.0%| Intercept| -3792.082| 17855.755| -0.212| 0.840| -49691.762| 42107.598| -49691.762| 42107.598| Cost of Pizza| -3174.060| 2093.357| -1.516| 0.190| -8555.205| 2207.086| -8555.205| 2207.086| Cost of Soda | -2266.736| 4129.036| -0.549| 0.607| -12880.761| 8347.289| -12880.761| 8347.289| Income Average Per House Hold | 0.035| 0.477| 0.073| 0.945| -1.192| 1.262| -1.192| 1.262| Population | 0.597| 0.437| 1.366|...
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