I would like some help answering the following, based on the data below. Succinctly and concisely make a recommendation that RACV Solar could consider to maximise revenue (i.e. maximise the value of System Cost).

DUMMY VARIABLES Complete the following table which summarises the results of your transformation of categorical variables into dummy variables. Number of Dummy IVs Remaining After Name of Remaining Dummy IVs After Transformation Categorical Variable Transformation #1 #2 #3 #4 #5 Method of Enquiry 2 Website RACV Store Sales Person 2 Anand Clayton Gender 2 Male Female Location 2 Geelong Surf Coast UNCORRELATED INDEPENDENT VARIABLES Complete the following table which summarises the independent variables which have been elimainated from the regression model due to being (virtually) uncorrelated with the Dependent variable (System Cost). Correlation Coefficient Independent Variable Eliminated (with DV) Conversion Period -0.0373 Male 0.0063 Female 0.0475 Cost of Current Consumption -0.0460 Annual Payoff -0.0179 Inquiry Other 0.0004MULTI-COLLINEARITY Complete the following table which summarises the independent variables (IVs) which have been eliminated from the regression model due to multi-collinearity (strongly correlated with each other). Correlation Coefficient of the Correlation Coefficient of Name of Independent Variable Eliminated from the Strongly Correlated Independent Variables Two IVs each IV with the DV Regression Model First Pair of RACV Store -0.8162 0.133957249 IV#2 Website IVs Website -0.122267659 Second Pair of Surf Coast -0.121680619 0.7317 IV #1 Surf Coast IVs Geelong 0.195753428 Third Pair of Revenue from Surplus ($) 0.278558029 0.833 IV#1 Revenue from Surplus IVs System Size (kW) 0.317780098 Fourth Pair of System Size (KW) 0.317780098 1 As both are having same correlation coefficient with DV, we IVs System Size (kW)2 0.317780098 will use only System Size (KW) Fifth Pair of First Independent Variable IV#1 CC with DV >0.70 or 0.70 or