My professor Said that I should run a histogram and scatter plot with this IPR (below) in SAS Studio.

Figure 1: Observed by Predicted for Rate Figure 2: Fit Diagnostics for Rate Fit Diagnosticsfor Rate Observed by Predictedfor Rate 15 4 10 5 4000 Raudert Raudert Residual -2 10 2 6 8 10 0.010 0.015 0.020 0.025 Redde Value Fedicte Value 100 0.08 - 900 20 10 0.06 15 Cock's D Rate Residual 0.04 - 10 In . 20 0 02 - Predided Value 5 -10 0.00 -3 -2 -1 0 2 3 0 5 10 5 20 0 50 100 150 200 250 Quantile Redaed Value Observation 30 Fit- Mean Residual 15 20 10 Observations 248 Parameters Per cent 5 Error DF 245 10 M SE 14.684 R-Square 0.3291 5 Adj R-Square 0 .3236 0 - -11 25 -3.75 3.75 11.25 0.0 0.4 08 0.0 04 08 Residual Poportion LessFIT CURVES Regression Loess Penalized B-spline . MARKERS XAXIS YAXIS ` TITLE AND FOOTNOTE GRAPH SIZEProgram 1 x IRP Linear Regression.ctk x *Characterize Settings Code/Results Split * DATA APPEARANCE INFORMATION DATA 153319.SYPHILIS DATA SET 7 Filter: (none) - ROLES * Analysis variable: (1 item) 123 Rate Scale: Percent (default) ADDITIONAL ROLESDATA APPEARANCE INFORMATION DATA IS3319.SYPHILIS DATA SET 7 Filter: (none) - ROLES *X axis: (1 item) 123 Rate *Y axis: (1 item) A Gender Group: (1 item) A Gender Legend location: Outside (default) ADDITIONAL ROLES