Present the model and your results visually, and also explain why the factors you chose in your regression analysis are critical for understanding this issue. Also, make recommendations f
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Get it written →Present the model and your results visually, and also explain why the factors you chose in your regression analysis are critical for understanding this issue. Also, make recommendations for action based on the results of your analysis. ( regression lab is attached)
Submit a Word document that is 45 pages in length, single-spaced, in 12-point Times New Roman font.
Lab 4: Logistic Regression Lab Heres the formula used in R : glm(formula = Victim ~ Age * Social_Net * Firewall, family = binomial(logit), data = Cybercrime_Dataset_clean)This model explains that age is the significant in this model. It shows with an 1 year increase in age there a 3% deduction in log odds likelihood of being victimized; that result was .03. When the exponent is increased the odds are greater. For example, when I plugged in 6% into excel to calculate the log odds increased to .82.Let me further explain, this means the chance of being a victim or not, decreased by 3% – with a 1 yr age increase. Age has the greatest increase in significance compared to all other factors presented in this chart. Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 1.000748 0.288767 3.466 0.000529 ***Age -0.031092 0.005226 -5.950 2.69e-09 ***Social_NetYes 0.637546 0.327915 1.944 0.051866 . Firewall -0.236183 0.365259 -0.647 0.517880 Age:Social_NetYes -0.002318 0.005950 -0.390 0.696804 Age:Firewall 0.002760 0.006803 0.406 0.685006 Social_NetYes:Firewall 0.094024 0.416586 0.226 0.821434 Age:Social_NetYes:Firewall -0.001824 0.007741 -0.236 0.813697
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