Schedule

Key resources: R for Data Science (2e) by Hadley Wickham, Mine Çetinkaya-Rundel, and Garrett Grolemund, Preceptor’s Primer for Bayesian Data Science by David Kane, Analyzing US Census Data: Methods, Maps, and Models in R by Kyle Walker, along with their their associated tutorials. Homework is due before midnight on the day before the class for which it is assigned.

See the home pages for the r4ds.tutorials, primer.tutorials, and tidycensus.tutorials for installation instructions.

Always reinstall the relevant package before starting a new tutorial. Example for r4ds.tutorials:

remove.packages("r4ds.tutorials")
remotes::install_github("PPBDS/r4ds.tutorials")

We are always fixing mistakes. You want to use the latest version.

Completed tutorials are submitted via this Google form. If you do not complete the tutorials on time, you will be removed from the class. Send in your tutorial answers saved in HTML format. Please try to ensure that the name of the file is the default name, like getting-started_answers.html. Avoid using the name which will be assigned to the file if you download the same answers twice (or more), stuff like getting-started_answers (2).html. You can just change the name of the file by hand if this happens.

The listed assignments are the tutorials. We also recommend that you read the associated chapters in the various textbooks, but there is no reasonable way for us to confirm that you have done so. Tutorial numbers/titles almost always match textbook chapter numbers/titles.

Week 1: January 6

Class will meet in Monday, Tuesday and Wednesday this week.

Monday

Try to set up your computer before class on Monday by reading the “Getting Started” chapter from the Primer.

Tuesday

  • Submit the “Getting Started with Tutorials” tutorial from the tutorial.helpers package. See the “Getting Started” chapter for details.

Reminder: All work must be completed by midnight the previous evening. Failure to submit your tutorial answers will result in you being removed from the course. It is not fair to your fellow students, with whom you will be working in small groups, for you to not be prepared for class.

Wednesday

  • From the r4ds.tutorials package, complete these tutorials: “Introduction,” “Data Visualization” and “RStudio and Code.”

Thursday

  • From the r4ds.tutorials package, complete three tutorials: “RStudio and Quarto,” “Data Transformation,” and “RStudio and Github Introduction.”

Friday

  • From the r4ds.tutorials package, complete these tutorials: “RStudio and Github Advanced,” “Data Tidying,” and “Terminal.”

Week 2: January 13

We meet Wednesday, Thursday, and Friday this week. But, as always, you have work due every weekday. Highlight is the presentation of your first project on Friday.

Monday

Tuesday

  • From the r4ds.tutorials package, complete these tutorials: “Quarto Websites Introduction” and “Quarto Websites Advanced.”

Thursday

  • From the r4ds.tutorials package, complete these tutorials: “Getting help,” “Layers,” “Exploratory data analysis,” and “Communication.”

Friday

  • From the tidycensus.tutorials package, complete these tutorials: “Exploring US Census data with visualization” and “Census geographic data and applications in R.”

Week 3: January 20

We meet Wednesday, Thursday, and Friday this week. But you still have assignments due every day. Recall that assignments are due at midnight on the day before the relevant class.

Monday

  • From the r4ds.tutorials package, complete these tutorials: “Logical vectors,” and “Numbers,” and “Strings.”

Tuesday

  • From the r4ds.tutorials package, complete these tutorials: “Regulars expressions,” “Factors,” and “Dates and times.”

Wednesday

  • From the r4ds.tutorials package, complete these tutorials: “Missing values,” “Joins,” and “Spreadsheets.”

Thursday

  • From the r4ds.tutorials package, complete these tutorials: “Databases,” “Arrow,” and “Hierarchical data.”

Friday

  • From the r4ds.tutorials package, complete these tutorials: “Web scraping,” “Functions,” “Iteration,” and “A field guide to base R.”

Week 4: January 27

We meet Monday, Tuesday, and Wednesday this week.

Monday

  • Have a rough draft of your second project ready to display in class.

  • Complete the “Data Project” tutorial from the primer.tutorials package. Be sure to reinstall the package before starting the tutorial. This the second time you have completed this tutorial.

Tuesday

  • Zoom presentation of your second project. I hope that, depending on student schedules, that we will do this in the evening, the better to allow for attendance from your family/friends from home. You are required to invite at least some family members to attend.

Wednesday

  • In-person presentation of your second project, conducted during class. You are required to invite at least some friends from campus to attend.