Subject details

  • Topics
    • Introduction to R and RStudio
    • R data types and basic syntax
    • Principles of programming - pseudo-code, comment, structures
    • Programming basics - functions, algorithms, loops
    • Data summaries and graphics
    • Hypothesis testing and comparison of means
    • Probability distributions and simulation in R
    • Simple linear regression
    • Categorical data analysis
  • Study resources
    • Instructional Methods
      • Disscusion forum/Discussion Board
      • Online Quizzes/Tests
      • Online assignment submission
      • Web links
    • Print Materials
      • Welcome letter
    • Online Materials
      • Printable format materials

Students who successfully complete this subject will be able to:

  1. Perform basic programming using R within the RStudio environment
  2. Demonstrate ability to write user-defined R programming functions
  3. Visualise data graphically using R
  4. Write R programs to conduct hypothesis testing and compare means using R
  5. Simulate data from different probability distributions.
  6. Perform simple linear regression using R
  7. Analyse categorical data using R.
  • Assignment 1 - Assignments — 2 (40%)
  • Assignment 2 - Invigilated Exam (50%)
  • Assignment 3 - Quizzes — Online Quizzes (10%)

Textbooks are subject to change within the academic year. Students are advised to purchase their books no earlier than one to two months before the start of a subject

Entry Requirements

Equivalent Subjects

You cannot enrol in this unit if you have successfully completed any of the following subject(s) because they are considered academically equivalent:

  • SWI-HMS772

Special requirements

No special requirements

This subject introduces R, one of the popular open source statistical programming languages commonly used in applied statistics and data science disciplines. Students will learn key programming principles of R and develop competence in programming in R which are essential for a statistician or data scientist to perform different types of statistical analyses.

Please note: assessment values are indicative only, details will be advised at the start of the subject.

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