Now assume that you want to regress income on an arbitrary number of explanatory variables available...

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Now assume that you want to regress income on an arbitrary number of explanatory variables available to you in a separate dataset. You choose to do so with a linear regression model. You consider different transformations of the data as well as differing choices of explanatory variables and calculate the following model selection criteria for your two favourite candidate models: 1110 reasonabIC R Criterion Model 1 Model 2 R 0.458 0.469 Radj 0.4323 0.4581 AIC 391.002 360.409 based on the calculated model selecti g) Assume that model 1 and 2 are both based on 200 observations. How many parameters does each model have based on the table above? Since the values in the table have been rounded, you will have to round your answer in turn. Now assume that you want to regress income on an arbitrary number of explanatory variables available to you in a separate dataset. You choose to do so with a linear regression model. You consider different transformations of the data as well as differing choices of explanatory variables and calculate the following model selection criteria for your two favourite candidate models: 1110 reasonabIC R Criterion Model 1 Model 2 R 0.458 0.469 Radj 0.4323 0.4581 AIC 391.002 360.409 based on the calculated model selecti g) Assume that model 1 and 2 are both based on 200 observations. How many parameters does each model have based on the table above? Since the values in the table have been rounded, you will have to round your answer in turn.