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Modern Statistical Programming

Course Description

Statistical analysis and data manipulation in R and Python. Implementation of SQL. Topics include data input/output; data formats and types; data management; functions for statistical modeling; introduction to algorithms; flow control and program design; and programs for complex data manipulation and analysis. Additional topics may include MATLAB and parallel computing.

Additional Requirements for Graduate Students:
Additional and/or alternative problems of a more challenging nature will be required for graduate students on homework assignments and exams.

Athena Title

Modern Statistical Programming

Equivalent Courses

Not open to students with credit in STAT 4365E or STAT 6365E

Undergraduate Prerequisite

STAT 2010 or STAT 2100H or STAT 2360-2360L

Graduate Prerequisite

STAT 6220 or STAT 4230/6230 or STAT 6315 or STAT 6315E or STAT 6420 or STAT 8200 or permission of department

Semester Course Offered

Offered fall, spring and summer

Grading System

A - F (Traditional)

Student Learning Outcomes

  • Students will read in data, clean it, and format it for analysis in R and Python.
  • Students will implement complex data visualizations in R and Python.
  • Students will manipulate data sets to extract the information needed for a desired analysis in R and Python.
  • Students will use standard programming techniques such as loops, conditional execution, and functions in complex data analysis in R and Python.
  • Students will create user-friendly graphical interfaces to programs conducting complex data analysis and visualization.
  • Students will identify and correct problems in their computer programs.
  • Students will access a data base, run queries, and write simple programs using SQL.

Topical Outline

  • Data input/output
  • Data formats and types
  • Data management
  • Basic procedures, functions for statistical modeling, inference, and statistical graphics
  • Introduction to algorithms, flow control, conditional execution, and program design
  • Accessing data using SQL
  • Writing programs for more complex data manipulation and analysis
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