Criteria for Assessing Goodness of Fit Criterion DF Value Value/DF Deviance 10 1519.9555 151.9956 Scaled Deviance 10 1519.9555 151.9956 Pearson Chi-Square 10 1518.0254 151.8025 Scaled Pearson X2 10 1518.0254 151.8025 Log Likelihood 3337483.2437 Full Log Likelihood -898.0732 AIC (smaller is better) 1824.1464 AICC (smaller is better) 1870.8131 BIC (smaller is better) 1840.6392 Algorithm converged. Parameter Intercept year year DF 1 1 1 2019 2020 month 1 1 month 2 1 month 3 1 Analysis of Maximum Likelihood Parameter Estimates Standard Estimate Error Wald 95% Confidence Limits Wald Chi-Square Pr> Chisa 6.1235 0.0076 6.1086 6.1385 645296 <.0001 month scale the genmod procedure model information data set work. thefts distribution poisson link function log dependent variable offset logdays number of observations read used w n class level value design variables year o oooooo ooo oooooooooo ooooooooooo question marks present a suitable and write paragraph explaining significant patterns in reported for new south wales over two-year period. criteria assessing goodness fit criterion df deviance scaled pearson chi-square x2 likelihood full aic is better aicc bic algorithm converged. parameter intercept analysis maximum estimates standard estimate error wald confidence limits pr> Chisa 6.1235 0.0076 6.1086 6.1385 645296 <.0001 month scale the genmod procedure model information data set work. thefts distribution poisson link function log dependent variable offset logdays number of observations read used w n class level value design variables year o oooooo ooo oooooooooo ooooooooooo question marks present a suitable and write paragraph explaining significant patterns in reported for new south wales over two-year period>