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Programming and Data Literacy Using R


Course Description

Elementary statistical analysis and data manipulation in R. Topics include algorithms, programs, and computing in R. Fundamental techniques of program development in R. Programming projects and applications. Hands-on experience of data input/output and formatting, brief introduction to object-oriented programming, introduction to statistical computing and very elementary data analysis and graphics.


Athena Title

Program and Data Lit Using R


Prerequisite

STAT 2000 or STAT 2000E or STAT 2010 or STAT 2100H or BIOS 2010 or BIOS 2010E


Semester Course Offered

Offered fall and spring


Grading System

A - F (Traditional)


Student Learning Outcomes

  • This course will introduce students to the statistical software package R and train them in how to use its packages to manipulate and statistically analyze data.
  • Students who take this course will learn to install R and RStudio on personal computers.
  • Students who take this course will learn to read data from external files (e.g., Excel files).
  • Students who take this course will learn to enter data manually.
  • Students who take this course will learn to identify and use data formats, modes, and attributes.
  • Students who take this course will learn to manage data objects.
  • Students who take this course will learn to control flow and execution.
  • Students who take this course will learn to write functions.
  • Students who take this course will learn to design programs.
  • Students who take this course will learn to build statistical graphics.
  • Students who take this course will learn to implement exploratory data analysis (five-point summary, plots).
  • Students who take this course will learn to load packages and use functions for statistical modeling and inference.
  • Students who take this course will learn to understand the role of statistical software in conducting statistical analyses.
  • Students who take this course will learn to use properly output from statistical software to communicate the results of statistical analyses through oral and written means.
  • Students who take this course will learn to use R Markdown for report writing and reproducible analyses.
  • Students will demonstrate competence through individual or group programming projects, labs, and examinations throughout the course.

Topical Outline

  • Data input/output in R
  • Data formats and types
  • Data management
  • Vectors and matrices and arrays in R
  • Loop structure
  • Introduction to algorithms
  • Writing functions in R
  • Plotting in R

Syllabus