Computationally complex model

While you are not expected to build a computationally complex model, your work needs to show logical flow, and demonstrates the Bayesian analysis concepts discussed in the course. This includes the following: 1. Description of the problem: What is the problem you are trying to solve? What is the motivation and significance behind this? Why might your approach be useful here? 2. Description of your data: What are the variables of interest and their summary? What are some caveats of the data (such as data quality issues) that we need to be aware of, if any? 3. Formulation of your analysis approach: How is the model or estimation algorithm defined? 4. Computational approach: What methods are you using to analyze the data? You are encouraged to use existing R packages. 5. Results and conclusion: What is the takeaway from your analysis? What makes your approach advantageous (or challenging) in your problem? What are the next steps in your analysis?