R

RStudio and R Markdown Notebooks

1. Create a R Markdown Notebook in RStudio.
2. Recognize the syntax for, create, and run code chunks in an R Markdown document.

Data Management in R

1. Load in a .rda file into an R session.
2. Access columns of a data frame using $ notation.
3. Access columns, rows, and elements of a data frame using dafr[i, j] ‘matrix’ notation.

Package Management in R

1. Install a package from the Comprehensive R Archive Network (CRAN) using install.packages.
2. Load a package into an R session using load.

mosaic and ggformula

1. State the ‘grammar’ of a command in ggformula.
2. Use the graphing functionality of ggformula to create univariate summaries of data, including:
   • rug plots
   • histograms
   • density plots
   • scatter plots
3. Use the graphing functionality of ggformula to create bivariate summaries of data, including:
   • scatter plots
   • nonparametric smoothers
   • linear regression lines
4. Use the %>% operator from magrittr package to overlay multiple graphics in the same plot.

knitr, LaTeX, and MathPix Snip

1. Knit an R Markdown document into a PDF or HTML file.
2. Recognize the two main “modes” for math in LaTeX.
3. Pronounce LaTeX correctly (“lay”-“tek”).
4. Typeset basic mathematical expressions using LaTeX.
5. Use MathPix Snip to generate LaTeX expressions from handwritten and typeset mathematical expressions.