You’re hired (by DALMI)!

Now that you have been working with the Paris Paintings dataset for a while, it’s time to put everything that you have learned to use.

Your task for this homework assignment is quite open ended – almost like a mini project. You will fit one (more extensive) multiple linear regression model predicting a numerical variable, and one (much simpler) logistic regression predicting the one of the categorical variables with NAs in your dataset. Note that the categorical variable should either only have two levels, or you should convert it to a two level categorical variable.

Overall you should accomplish two tasks: * main focus: explore and discuss relationships in the variables that tell us something meaningful about the auction market in Paris in these years * side focus: predict values for some NAs in the dataset

Over the weekend post on Piazza your ideas and Hilary and Sandra will chime in on whether the relationships you decide to focus on are of interest, and if not, how your approach can be tweaked. Each team must post once on Piazza by 9am Sunday morning. You don’t have to have your analysis completed at this time, just need to have a sketch of your plan of attack.

As usual, be creative, and use visualizations to support your narrative.

Data:

The data set you will need for this assignment can be found at https://stat.duke.edu/courses/Fall14/sta112.01/data/paris_paintings.html.

Deliverables:

As usual, you should complete your analysis in R / RMarkdown, and turn in a fully reproducible report. Submit your Rmd and HTML files on Sakai. Your Rmd file should use paris_paintings.csv as the input data, so that I can reproduce your work with the dataset and the code included in your Rmd file.

Honor code:

This is a team assignment. In this assigment we want you to limit any specific discussion on model selection to your team only, though you are allowed to have general conversations with other teams. As usual, all calculations, R code, and writing must only be shared within the team. Failure to abide by these policies will result in a 0 for everyone involved. If you borrow code from an online source, make sure to cite it using a comment in your code. The comment should be visible in the HTML output.

Support:

Besides sharing ideas between each other, you can ask questions on Piazza or come by office hours. If your question is related to a code error make sure to post a MWE (minimum working example) on Piazza so that others can recreate your issue. Office hours before the assignment is due:

  • Hilary and Sandra: ???
  • Dr. Çetinkaya-Rundel: Monday 4-5pm or by appointment