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In this practice, you use the PVA data set to build and refine a linear regression model. This model attempts to predict the amount

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In this practice, you use the PVA data set to build and refine a linear regression model. This model attempts to predict the amount of donation given to the PVA. These practices provide practice for using SAS Visual Statistics to do exploratory modeling. a. Practice setup: Create the initial linear regression model. 1) Launch Visual Analytics or start a new report. 2) Select the PVA data source and open it. 3) Start a linear regression, disable auto-refresh, and assign the variable roles as follows: Response: Target Gift Amount (one total) Continuous effects: All variables except two that begin with Target Gift (21 total) Classification effects: Gender, Home Owner (two total) 4) Enable auto-refresh to run the model. b. How many observations were used to build the linear regression model? c. What is the R-square and the adjusted R-square of the model? d. Modify variable measures. In order to change the classification of a variable, it cannot be assigned to an object. Remove Status Category Star All Months from the model before you modify its classification. 1) In the Roles pane, remove Status Category Star All Months from the continuous effects.

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