uscots2021_presentation

Materials for the USCOTS 2021 Breakout Session

Requested materials

The following materials were requested from attendees during our talk. We are happy to share.

• Copy of the syllabus from Spring 2021
• Copy of Homework #0 (typically assigned the week before classes start)
• Copy of Homework #1 (typically due near the start of week 2)

A second course in statistics: Bridging data science and statistical modeling

Materials for the USCOTS 2021 breakout session, "A second course in statistics: Bridging data science and statistical modeling," will be made available here.

Materials for Session

The materials will be presented through some slides and a knitted RMarkdown file.

• The slides used in the presentation are available here
• Participants are highly encouraged to download the Markdown file uscots_assignment_starter.rmd (right-click, save link as...) and participate in the session.
• A fully worked out (solution set) version of the assignment is available here
  • Also available for download (right-click, save link as...").

Schedule of our session

Below is a rough schedule for the breakout session.

2:30-2:33 - Presenter introductions

2:33-2:50 - Class time! - We will present some materials using an RMarkdown file. The materials are chosen to reasonably mimic a typical class.

2:50-3:15 - Class structure discussion. We will overview the history of the class including its recent increase in enrollment and the adoption of pseudo-inverted classroom design.

3:15-3:35 - Back to class, participants will go to Zoom Breakout rooms to have the opportunity to work on the "in-class assignment". The three presenters will work as faculty hopping around breakout rooms to help and discuss.

3:35-3:45 - Open discussion of all that is covered.

Software needed

In this session we will be using the R language for Statistical Computing and RStudio (an IDE for coding in R). Specifically we will be working with RMarkdown. For those interested in participating please install:

• R from https://cran.r-project.org/
• RStudio from https://rstudio.com/

R Packages

In addition to the base language of R, we will use the following add-on packages

• tidyverse
• ggfortify
• GGally
• knitr

You can install all these packages in R/RStudio with the command install.packages(c("tidyverse", "ggfortify", "GGally", "knitr") ). If asked to install from source, select No.

Textbook

The course that will be discussed in this Breakout session, STA 363, uses this online text authored by two of the presenters.