I am highly confused on how to understand these findings in my IS3310 class at Troy. It is for my research project. Especially how to red the plot figures. Will you help me to interpret this for my IRP?

Starting Observations: Observed by hedi ded for Rate I ran a correlation analysis (Table 1) that contained 4 variables (Count, Population, Rate). Coefficients, N=248. My findings were that there are negative correlations Population and Count. There are no negative coefficients. 20 I used SAS to run a linear aggression. My number of observations read and used (Table 2) are the same, 248. I used 1 classification value (Table 3), which was Gender. Gender has 2 values. I observed in the Analysis of Variance that the F- value is 60.08 and the P-value is <.0001 making it significant. the r-square is and root mse observing parameter estimates i find interlope value pale looked at observed ve. predicted that variances are equal there no significant differences in risk for syphilis men vs. women. residual found normal distribution of error terms. table correlation pearson coefficients n="248" count population rate vale figure fit diagnostics number observations read r3 udem paudem rcidual used classification level information class predided fredided levels values gender female male standard variable label df estimate t pr> 959% Confidence Limits Predicted Value Observation Intercept Intercept 2.06760 2.59254 12.3 :.0001 26.96108 37.17411 Fi- Me Population Population -183995E-7 1.887442E-8 -9.75 <.0001 is gender female paoant paramed as male bt or df use r-sjs>