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Topics Covered in Graduate Statistics Programming Courses

STAT 510 SAS Programming I

Prerequisite: familiarity with computer basics

  • Reading external data files into SAS
  • Creating permanent SAS data sets
  • Formatting and labeling variables
  • Using Excel through SAS
  • Conditional processing
  • Do loops
  • Subsetting and combining data sets
  • Using numeric and character functions
  • Arrays
  • Displaying data and customizing reports
  • Summarizing results
  • Frequencies
  • Tables
  • Graphing

STAT 514 R Programming

Prerequisite: familiarity with computer basics

  • R installation and environment
  • Data structure, management, and manipulation
  • Logic statements (if else)
  • Basic loops (for, repeat, while, do until)
  • Use of in‐built functions
  • Basic custom function writing
  • Installation of extensions to R
  • Intermediate programming techniques
    • apply, lapply, sapply

STAT 592 Data Visualization with R

Prerequisite: STAT 514

  • Data importation and formatting
  • Data visualization
    • Base graphics
  • Plot, boxplot, hist, lines, points, etc.
  • Use of par for graphical parameters
  • GGplot2
    • Qplot
    • Basic grammar
    • Plotting with layers
    • Graphical parameters

STAT 600 Statistical Programming

Prerequisite: STAT 541

  • R programming
    • Formatting
    • Aggregation
    • Loops
    • Dynamic report generation (Sweave/Knitr)
    • External data sources
  • SAS programming
    • Defining and using macro variables and macros
    • PROC SQL in Macros
    • Graphing in SAS