see picture of "State Crime": row 2 gives detailed descriptions of each variable, while row 4 gives short versions that should be used in your regressions. 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. Use "Robbery" as your dependent variable in each model. 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: Robbery = f(Murder, Population, %Metro)

Model B: Robbery = f(%Bachelors, %Metro, %SameHouse, %young)

Model C: Robbery = f(%Bachelors, %Metro, %SameHouse, %youngmale)

Model D: Robbery = f(%Bachelors, %Metro, %SameHouse, %youngfemale)

Model E: Robbery = f(MedianAge, %Poverty, %Unemploy, Rain)

Model F: Robbery = f(MedianAge, %Poverty, %Unemploy, Temp)

Model G: Robbery = f(MedianAge, %Poverty, %Unemploy, Sun)

The state of North Utah currently has a median age of 37.4, a 12.7% poverty rate, a 6.1% unemployment rate, and 41.9 inches of annual rainfall on average. Recent economic changes have led to the unemployment rate falling to 5.8%. This change will likely be associated with the Robbery rate changing from about 77.6 robberies (per 100,000 inhabitants) to about ___ robberies.