Centre for Continuing Education

Introduction to R Programming Course

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The ability to extract useful insights from large amounts of data is rapidly becoming one of the most highly valued skills in modern information workers. This growing demand is reflected in the increasing ubiquity of R in business, government and academia.

Learning R will turn you into a data surgeon, able to examine, filter, transform and visualise datasets in ways simply not possible with spreadsheets or relational databases. With the proliferation of user-friendly software environments such as RStudio, and increasing support for R from companies such as Microsoft and Oracle, it’s easier than ever to get started. This course will give you a solid foundation in R and equip you to deploy it for your own analytics needs.

Aims

This course aims to give participants:

  • A working familiarity with the R language
  • The ability to perform basic data transformation, analysis and visualisation with R
  • A framework for applying R to their own domain-specific problems
  • An introduction to resources for continuing to develop their R skill set.

Outcomes

Upon successful completion of this course, participants should be able to:

  1. Use RStudio to write and run R code.
  2. Write syntactically correct R expressions that involve variables, variable assignment, operators and functions.
  3. Identify basic R data types (character, double, integer and logical).
  4. Identify basic R data structures relevant to modern data analysis (atomic vectors and data frames).
  5. Find, install and use R packages.
  6. Import data into R.
  7. Apply the basic verbs of data transformation (filtering, selecting, mutating, renaming and arranging).
  8. Apply the ‘split-apply-combine’ method of data analysis.
  9. Identify the components of a statistical graphic according to the “grammar of graphics”.
  10. Create statistical graphics with ggplot2.
  11. Find and read documentation for R packages and functions.

Content

This course covers the following topics:

  • Introduction to R and RStudio
  • Performing arithmetic and variable assignment
  • Understanding, creating and using vectors
  • Understanding and performing vectorised operations
  • Understanding and identifying the different types of vector
  • Using functions
  • Finding and reading function documentation
  • Understanding and identifying common data structures
  • Finding, installing and loading R packages
  • Importing data from a file into R
  • Filtering datasets
  • Summarising datasets
  • Understanding and applying the split-apply-combine strategy
  • Drawing statistical graphics.

Intended Audience

This course is suitable for:

  • Business and IT professionals looking to improve their data analysis and automation skills, or to address a particular business need.
  • Government and other administrative professionals who work with big data, and in particular those who frequently need to present reports and data visualisations, an area in which R is particularly strong.

Prerequisites

It is assumed participants have computer and data literacy knowledge to the level of performing basic data analysis tasks in Microsoft Excel. No previous programming experience is required.

Delivery Style

This course is delivered as presenter-taught computer-based training in a computer lab. It will involve a mixture of didactic and interactive activities in a variety of learning modes. Participants will spend most of the course time interacting with R on their individual workstations, asking questions and discussing issues as they arise. Between and during these interactive exercises, new material will be delivered verbally by the instructor, with demonstrations on a screen projector showing a live R session. Key concepts will also be developed on the whiteboard with tables and diagrams.

Materials

Participants will be provided with a hard-copy workbook including a mixture of explanations and demonstration code which they can refer to at their own pace.

Recommended Reading

Teetor, P. 2011, R Cookbook, O’Reilly, Sebastapol.

Wickham, H. 2015, Advanced R, CRC Press, Boca Raton.

Wickham, H. 2016, ggplot2, 2nd ed., Springer.

Wickham, H. & Grolemund, G. 2016, R for Data Science, O’Reilly, Sebastopol.

Features

  • Free repeat class - Conditions apply
  • Free USB flash drive
  • Expert trainer
  • Dedicated computer for every student
  • Small class size
  • Student notes – yours to keep
  • Statement of completion