Download the "Soft Drink Consumption" Excel sheet. Estimate the following multiple regression models (remember that all of your independent variables will have to be in adjacent columns in Excel). Look at each set of results critically and consider how you would interpret the strengths and weaknesses of each model. Save your results from each model for use when completing the end-of-module assessment. C, the dependent variable, will always be "Consumption of Soft Drinks per Capita;" for independent variables, use the following specifications. (The notation f(X, Y, Z) means "a function of X, Y, Z; i.e., X, Y, and Z are your independent variables. Even though it isn't listed, each model will include an intercept.) NOTE: when Excel reports a value like 2.4E-06, this is scientific notation for 2.4 * (10^-6), or 0.0000024.
Model A: C = f(population 2008, per capita income, % obese adults)
Model B: C = f(physicians, % smokers total)
Model C: C = f(physicians, % male smokers)
Model D: C = f(physicians, % female smokers)
Model E: C = f(mean annual temp, number of food businesses, per capita income)
Model F: C = f(mean annual temp, number of food businesses, per capita income, dentists)
Model G: C = f(mean annual temp, number of food businesses, per capita income, physicians)
The state of West Dakota currently has mean annual temperature of 55 degrees, 4600 food service businesses, $17 thousand in per capita income, and 0.65 dentists per 1000 people. The state suddenly experiences a surge in its dentist graduation rate, and increases its dentist density to 0.7 per 1000 people. This surge will likely be associated with soft drink consumption falling from about 171 drinks annually to about ___ drinks annually (round to nearest whole number, no decimals).