Regression: Soft Drink Demand

Topics: Supply and demand, Linear regression, Statistics Pages: 3 (753 words) Published: March 28, 2013
Soft Drink Demand Estimation
Demand can be estimated with experimental data, time series data or cross section data. Sara Lee Corporation generates experimental data in test stores where the effect of an NFL-licensed Carolina Panthers logo on Champion sweatshirt sales can be carefully monitored. Demand forecasts usually rely on time series data. In contrast, cross-section data appear in Table 1. Soft drink consumption in cans per year is related to six pack price, income per capita, and mean temperature across the 48 contiguous sates in the United States Question

1. Estimate the demand for soft drinks using a multiple regression program available on your computer. 2. Interpret the coefficients and calculate the price elasticity of soft drink demand 3. Omit price from the regression equation and observe the bias introduced into the parameter estimate for income. 4. Now omit both price and temperature from the regression equation. Should a marketing plan for soft drinks be designed that relocates most canned drink machines into low income neighborhoods? Why or Why not? DATA SET 2

The data are the results of the following market research experiment by a large company. The company’s total market area was divided into 40 equally populated market areas, and the price to be charged for the product was set to be the same in each area. Then, the weekly amount of advertising expenditure ($) in each of these market areas was set as indicated in column B. The weekly sales (y units) in each market area was then recorded as shown in column C. 1. Use linear regression to estimate a linear equation describing how the value of sales (y) varies with the level of the fitted equation. 2. Assess the validity of the fitted equation.

3. If the product sells at a price of $100 and costs $70 per unit to produce, estimate a linear equation for the company’s weekly profit in terms of its advertising expenditure (x).

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