Please answer following:

What is the unstandardized prediction formula for this regression model? Please use values from the table in your answer. Report these values exactly as they are seen on the table to 2 decimals. Make sure to include negative signs if necessary. (x1)+ (x2)+ (x3)+ (x4)+ (365) H) II + What is the unstandardized prediction formula for crime rate for Southern states? Fill out the "fitted" or condensed version of the prediction formula that should be used to predict crime rate for only Southern states, combining together predictors where necessary and appropriate. Values to 2 decimal places. (x1)+ (x2) \\1) II + Predict the violent crime rate for a Southern state with an urbanization = 55.4 and poverty = 13.7. Answer to 2 decimals. What is the unstandardized prediction formula for crime rate for non-Southern states? Fill out the "fitted" or condensed version of the prediction formula that should be used to predict crime rate for only non-Southern states, combining together predictors where necessary and appropriate. Values to 2 decimal places. E) II + (x1)+ (x2) Predict the violent crime rate for a non-Southern state with an urbanization = 65.6 and poverty = 8.0. Answer to 2 decimals. Data from the 50 states plus the District of Columbia (n = 51) were analyzed to evaluate if violent crime rate (per 100,000 persons per year) could be predicted from the quantitative variables of urbanization (percent of the population living in urban areas) and poverty rate. A categorical predictor indicating whether or not a state is classied as a Southern state (1 = Southern. 0 = not) was also used, and two interactions were generated with this variable (Urban X South and Poverty X South). Some output is shown below. Use this information to answer the questions below. Use or = 0.05. Model Beta Std. Error t-value Sig (Intercept) -321.90 148.20 -2.17 0.035 Urban 4.69 1.65 2.84 0.007 Poverty 39.34 13.52 2.91 0.006 South (S = 1) -649.30 266.96 -2.43 0.019 Urban X South 12.05 2.87 4.20 0.000 Poverty X South -5.84 16.67 -0.35 0.728 Assume x1 = Urban, x2 = Poverty, x3 = South, x4 = Urban X South, x5 = Poverty X South