Immigration and Crime Rates Regression Analysis

Topic is Exploring the Relationship between Immigration Rates and Crime Rates in U.S. Cities or The Relationship between Immigration Rates and Crime Rates in U.S. Cities. You can alter it slightly if you need to based on data availability. ** Please find relevant data from official sources for this project. below is the rublic, please follow that. ** Please use one or two sets of data for this project. **Please use Minitab for charts, graphs, regression results, etc. In the Final Project you will build and perform regression diagnostics on several models in order to determine the most appropriate set of predictors and subsequently the most appropriate model. You must choose a topic of interest drawn from real-life experiences. You must collect data for this project and complete the following: Identify your variables, and categorize your response and predictors (qualitative and quantitative predictors). You must produce a scatterplot of the outcome variable versus each of the predictors. Conduct a first-order main effects model. Conduct an analysis of the model using regression diagnostics to determine whether the model is appropriate. Determine which additional terms (higher-order or interaction) should be included. You may go through several iterations of this process before you decide on your final model. Your final model must have at least one quantitative variable and one qualitative variable. Perform a nested F-test on your final model and a reduced model of your choice to show that the final model is the better one. Use your findings from the above model building and resulting analysis and write a paper summarizing your findings. Include relevant Minitab output (charts, graphs, regression results) in your statistical regression report. Refer to module content and the case studies in your text for additional resources. Your paper must including the following parts: Introduction: Include your topic, your variables, an overall description of your data, the means of collecting data, and what you hope to achieve in your findings. Include any predictions as needed. Regression Model Building: Describe the results of the model you built. You must include the following information about both the first-order main effects model and the final model: A scatterplot of the outcome vs. predictor variables The model equation in general form The complete regression output from Minitab including any unusual predictors A written explanation of why the model was/was not chosen (i.e., why those predictors were selected) The R2 value and its interpretation Regression diagnostics and your impression of them The interpretation of each of the coefficients included in the final model Testing Model and Comparison of Models: Looking at your variables, only include those variables that are necessary. Conduct a reduced model as needed. Perform a nested model F-test on your final model compared to the researcher’s suggested model. Explain why the outcome of this test shows that your model is the more appropriate one. Compare and contrast the original model and the final model and discuss the strengths or weaknesses of both based on R2 and the regression diagnostics. Also comment on the importance of an iterative model-building process. Particularly pay attention to the reasons why it is imperative that each model built is carefully examined. What are the implications of just using the first model built? Conclusion: Interpret your results in context of your topic.

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