Stats analysis and a paper

The Excel file contains 1000 observations of demand data Write up your results in a 5-7 page paper. Create an interesting story behind it (e.g. you own a pizza parlor and monitored demand data over the past 3 months) and include the following: 1) summarize the data 2) run a correlation of the data 3) graph any interesting relationships of two variables 4) run a simple OLS regression 5) run a multiple regression 6) run different multiple regressions 7) calculate the variance inflation factor (VIF) for you multiple regression 8) provide a residual plot to show normality of residuals 9) run a linktest on at least one regression and interpret your findings 10) run a Ramsey RESET test on the same regression model you ran the linktest and interpret your finds 11) check the residuals for presence of heteroskedasticity on at least one regression 12) interpret the estimates for a linear and log-linear (double-log) 13) try a two stage least squares model with price being the endogenous variable Create tables for the regressions, summary stats, and correlation matrix. You can list the results of the specification tests in a separate section. Variable Definitions Quantity = the quantity of pizza consumed (in tens, e.g. if quantity = 400 then actual quantity = 4000) Price = price of the pizza income = the average income of town j compp = the price of a complementary good pop = the total population of town j labor = the wage rate per hour to make pizza cheese = the price of cheese per pound subp = the price of a competitor's pizza pop1000 = population scaled by 1000 inc1000 = income scaled by 1000 lnq = natural log of quantity lnp = natural log of pizza price lni = natural log of income lncp = natural log of competitor price lnpop = natural log of population lnsubp = natural log of competitor's price lnl = natural log of labor wage rate lnc = natural log of cheese price �