Making Decisions Based on Demand and Forecasting

Making Decisions Based on Demand and Forecasting

Vanesa Hulett

Strayer University

ECO550

Professor Francisco de Cossio

October 28, 2013

Use Excel or other calculation software to input the data 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 in your town or community. Explain any additional variables that may improve the coefficient of determination.

According to the online business dictionary, the coefficient of determination (R2) is a “statistical method that explains how much of the variability of a factor can be caused or explained by its relationship to another factor” (Business Dictionary, 2013, coefficient of determination). In other words, it is a ratio or percentage used with the purpose of predicting future outcomes or testing hypothesis. In regression, the coefficient of determination is a statistical measure of how well the regression line approximates the real data points.

After analyzing the regression statistics outcome from the Pizza Company data, the coefficient of determination was 0.832980642. This means that about 83% of the variability experienced in the demand of pizza is a result of variations in price (P), competitor’s price (Px), advertising (Ad), and income (I). There are still a 17% of possible variations in the demand whose variables are yet to be determined. By adding more variables to the model, the coefficient of determination will improve by providing more predictors to explain the variance.

Before making a decision, one should consider to include variables like the price of substitute goods such as frozen pizza, complementary goods such a sodas, the size of the potential population, and consumer’s tastes or preferences. It can be somehow expensive to gather this data and information, but the managers will be making more informed decisions and minimize the risk of...