the data set includes information on the quantities consumed of this good (a proxy for the quantities demanded for this good), the price per unit of this good, the price per unit of at least one related good in consumption (substitute or complementary good), and a proxy for consumer income.
Attached is raw data and linear regression analysis. I have already done linear regression analysis
We don’t know what is the real demand for this good but we can use linear regression analysis to obtain parameter estimates of a linear approximation of it. In other words, if the unknown demand for this good is
QD = F (P; PR, M)
Where QD is the quantity demanded for this good, P is the price per unit, PR is the price of the related good(s) in consumption (substitute or complement) and M is consumer income.
A linear approximation of this demand equation is
QD = a b P c PR d M
You will use the data provided and excel (linear regression attached) to estimate the unknown parameters a, b, c, and d.
Then, you will use these parameters estimates and concepts to analyze the regression results and provide advice, recommendations and useful information to firms producing this good.
The final report will have the following basic format:
1. Introduction with goals and objectives.
2. Analytical and Empirical Frameworks