DescriptionIn this project you will write a report on a data analysis in which y

DescriptionIn this project you will write a report on a data analysis in which your main methodology will comprise of a collection of techniques taught in STA238 Summer 2021. The methodology must include the following: at least one simple linear regression;
at least one confifidence interval (either through a bootstrap or the Z/t approach);
at least one maximum likelihood estimation (which implies you need a frequentist model);
at least one hypothesis test;
at least one Bayesian credible interval (which implies you need a Bayesian model);
at least EITHER a maximum likelihood estimator derivation (for your maximum likelihood estimate)
OR a posterior distribution derivation (for your Bayesian model). Mathematical derivations should go in the appendix. Please keep in mind that this analysis is for our course. Thus the analysis should be to answer a question about an underlying random process we have data from. You will fifind some data, form an interesting question and answer the question through your analysis. Your question should be stated clearly so that the reader can quickly identify it in the introduction (and repeated maybe more formally as a hypothesis test in the methods section). In order to showcase all the difffferent methodologies listed above, you may need multiple research questions. However, all the research questions should relate to one another and be of similar topic areas. There should be no evidence that this is a class project, I should be able to take a screenshot of this and paste it into a newspaper/blog. There should be no raw code. All output, tables, fifigures, etc. should be nicely formatted. Make sure that the data is appropriate for your methods. Pick something that is interesting to investigate and has variables appropriate for the methodology you are going to perform. Again, the analysis should be to answer a question about an underlying random process we have data from. Please post on Piazza or email me at sta238@utoronto.ca for clarifification on appropriate data. The material and text on this project should be difffferent from that of your previous assignments in this course. Thus, you should NOT directly copy your previous assignment work. We highly encourage you use feedback from previous assignments to amend/proofread/update your Final Project. If your work is a direct copy of a previous submission or is a direct copy of another person’s submission this is considered an academic offffense.
Requirements: 1111