📝 HW5

Due date: Monday, November 25 at midnight.

⏳ We recommend reading through each problem ASAP so you can accurately estimate the time needed to complete the assignment.

Unless otherwise stated, assignments in STAT 131A are to be done individually.

Some components of this assignment have not been seen by a previous cohort of STAT 131A students, so there may be some unforeseen hiccups.

📮 Submission

Submit your assignment via Gradescope. The Gradescope will be live at least a few days before the HW deadline.

  • Make sure to tag your answers properly on Gradescope, or else you may be docked points for making the grading process more time-consuming.

You must submit a PDF of any PingPong chats that include code you used in your submission.

  • This should take the form of one long PDF. One way to do this is to copy all of your relevant PingPong chats into a Google Doc, and then print the doc as a PDF.

  • You are responsible for understanding all the code you submit, regardless of whether or not you used PingPong for help.

For the coding component, you will produce both (1) a .Rmd file with your code and (2) an PDF file containing the code and output.

  • On Gradescope, you will submit a single ZIP file containing both the .Rmd and PDF files.

  • To generate a PDF of your code and output, do not knit to PDF. Instead, knit your .Rmd file as HTML, open the HTML file in a web browser, and then print the HTML as a PDF, making sure that none of your code or output is cut off. You can generate an HTML file in RStudio by pressing Knit and then Knit to HTML.

  • The knitting process will not work if there are errors in your code, so be sure to leave plenty of time to knit your lab notebooks before the deadline.

  • Proofread your PDF to make sure all of your answers and plots are visible. If your PDF file is really long, it is possible that your code is printing out a large dataset or a really long vector. Make sure to comment out any code that prints more information than each question asks you for.

🔮 Inference and prediction with logistic regression and LPMs in R (100% of the HW5 grade)

DataHub

  • The HW5 coding problems are located in 131a-labs-fall-2024 directory.

GitHub