• Online, Self-Paced

R is a programming language used to carry out statistical analysis on datasets. This course covers the basics to get started with programming in R. This course demonstrates R using basic statistic functions, data handling, and visual representation through charts, graphs, and plots.

Learning Objectives

Introduction

  • start the course
  • install R in Microsoft Windows
  • install the RStudio IDE
  • navigate the R Console within the RStudio IDE
  • use the syntax for if-else, operators, loops, and the apply function in R
  • create and manipulate basic data types including numeric and string variables
  • use the vector and matrix types in R
  • install and use packages from the Comprehensive R Archive Network (CRAN)
  • create reusable user-defined functions in R
  • use the random number generator in R to generate single random numbers, random samples, and other random variates using the norm and binom functions

Debugging

  • use traceback and debug to track down errors in your R code
  • use the browser and recover functions to find bugs in R

Data Handling

  • read input and format output using the Console in R
  • import data from a CSV file in R
  • import data from an Excel spreadsheet in R
  • handle missing or unknown values in data problems in R
  • use the built-in examples to understand R functions

Basic Statistics

  • use the mean function in R
  • use the median function in R
  • use the mode function in R
  • use R to measure the spread and dispersion in a dataset
  • use R to measure the median absolute deviation
  • use R to measure covariance and correlation between two different datasets
  • use the R table function to cross tabulate data

Visualizing Data

  • use R to create pie charts from datasets
  • use R to create bar plots from datasets
  • use R to create box plots from datasets
  • use R to create histograms from datasets
  • use R to create line plots from datasets
  • use R to create scatter plots from datasets
  • use R to export graphics such as charts and plots for use in other software

Practice: Introduction to R Programming

  • understand the basics of the R statistical programming language

Framework Connections

The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):

Specialty Areas

  • Software Development

Specialty Areas have been removed from the NICE Framework. With the recent release of the new NICE Framework data, updates to courses are underway. Until this course can be updated, this historical information is provided to give better context as to how it can help you with your cybersecurity goals.

Feedback

If you would like to provide feedback for this course, please e-mail the NICCS SO at NICCS@hq.dhs.gov.