Topic Index

Meta

The following is a list of topics and skills covered during the semester. This will grow as we progress through the coursework. Italicized items are only covered in the readings. If you have additions or suggestions, please let Chris know!

A-D

• Analysis development (Course Preview, Lecture-01, Lecture-02, Lecture-03)
• Anscombe’s quartet (Lecture-03)
• Assignment (Lecture-01)
  • Assignment operator, <-
• base
  • Calculate mean, mean() (Lecture-03)
  • Create binary conditions, ifelse() (Lecture-02)
  • Frequency table, table() (Lecture-03)
  • Get names of object, names() (Lecture-01)
  • Load packages, library() (Lecture-01)
  • Maxmium value of vector, max() (Lecture-03)
  • Minimum value of vector, min() (Lecture-03)
  • Range values of vector, range() (Lecture-03)
  • Sort or order a vector, sort() (Lecture-01)
  • Summarize data frame or vector, summary() (Lecture-03)
  • View working directory path, getwd() (Lecture-01)
• cowsay (Lecture-01)
  • Creating ASCII character, say()
• Data
  • tidy data concepts (Lecture-01)
• Data cleaning
  • ordering (Lecture-02)
  • subsetting (Lecture-02)
  • variable creation and modification (Lecture-02)
  • see also dplyr
• datasets
  • Anscombe quartet data, datasets (Lecture-03)
  • Old Faithful geyser data, faithful (Lecture-01)
• Degrees of freedom (Lecture-03)
• Descriptive statistics (Lecture-03)
• dplyr
  • Create new variables, mutate() (Lecture-02)
    • see also base::ifelse()
  • Modify contents of existing variables, mutate() (Lecture-02)
  • Rename variables, rename() (Lecture-02)
  • Reorder variables, arrange() and desc() (Lecture-02)
  • Subset by columns, select() (Lecture-02)
  • Subset by observations, filter() (Lecture-02)
  • see also Operators

E-H

• Exploratory data analysis (Lecture-03)
• Getting help
  • With R, including ? and ?? (Lecture-01)
  • see also reprex and Reproducible examples
• ggplot2
  • Basic use
    • Create ggplot object, ggplot() (Lecture-02)
    • Change to horizontal, coord_flip() (Lecture-02)
    • Color and asthetic mappings, color and fill (Lecture-02)
    • Position adjustments, dodge and jitter (Lecture-02)
  • Geoms
    • Area plot, geom_area() (Lecture-02)
    • Bar plot, geom_bar() (Lecture-02)
    • Box plot, geom_box() (Lecture-02)
    • Density plot, geom_density() (Lecture-03)
    • Line plot, geom_freqpoly() (Lecture-02)
    • Scatter plot, geom_point() (Lecture-02)
    • Smoothed line plot, geom_smooth() (Lecture-02)
• GitHub
  • Basic use (Course Preview, Lecture-01)

I-L

• janitor
  • Frequency table, tabyl() (Lecture-03)
• knitr
  • With notebooks (Lecture-02)
• Levels of measurement (Course Preview)
  

M-P

• Magritter
  • see Operators, Pipe operator
• Model fit
  • Conceptual definition (Lecture-03)
  • Outliers and the mean (Lecture-03)
• Notebooks (Lecture-02)
• Operators
  • Arithmatic operators, +, -, *, /, and ^ (Lecture-02)
  • Logical operators, & and | (Lecture-02)
  • Pipe operator, %>% (Lecture-02)
  • Relational operators, <, >, <=, >=, ==, and != (Lecture-02)
• Package installation (Lecture-01)
  • From CRAN, see utils package entry
  • From GitHub, see remotes package entry
• Plotting and visualization
  • Basic elements of design (Lecture-02)
  • see also ggplot2

Q-T

• R
  • Basic use (Course Preview, Lecture-01)
  • Data cleaning (Lecture-02)
• remotes (Lecture-01)
  • Install packages from GitHub, install_github()
• reprex
  • Produce reproducible example, reprex() (Lecture-03)
• Reproducible Examples (Lecture-03)
• Reproducibility (Course Preview, Lecture-03)
• rmarkdown (Course Preview, Lecture-02)
• skimr
  • Produce descriptive statistics table, skim() (Lecture-03)
• stats
  • Calculate median, median() (Lecture-03)
  • Calculate standard deviation, sd() (Lecture-03)
  • Calculate variance, var() (Lecture-03)
  • Calculate inter-quartile range, IQR() (Lecture-03)
• Summation notation (Lecture-03)
• testDriveR
  • Automobile data for 2017, auto17 (Lecture-01, Lecture-02)

U-Z

• utils (Lecture-01)
  • Install packages from CRAN, install.packages() (Lecture-01)
  • Print
    • first six observations, head() (Lecture-02)
    • last six observations, tail() (Lecture-02)
  • Structure of an object, str() (Lecture-01)
  • Spreadsheet-like data view, View() (Lecture-01)
  • Update packages from CRAN, update.packages() (Lecture-01)
• Version control (Course Preview)
  
• Workflow (Course Preview)