Overview
Learn essential skills for handling, visualising, and analysing data. These skills are important in the physical and life sciences, commerce, and humanities.
This course introduces the fundamentals of data science through practical work in the R programming environment. Students will learn to import, manage and analyse data while developing skills in programming, visualisation and modelling. Emphasis is placed on the full data science workflow - from data preparation to communication - highlighting how computational tools support modern statistical practice.
About this paper
| Paper title | R for Statistics and Data Science |
|---|---|
| Subject | Computer and Information Science |
| EFTS | 0.1500 |
| Points | 18 points |
| Teaching period | Semester 2 (On campus) |
| Domestic Tuition Fees | Tuition Fees for 2027 have not yet been set |
| International Tuition Fees | Tuition Fees for international students are elsewhere on this website. |
- Prerequisite
- One of STAT 110, STAT 115, MATH 130, COMO 101, COMP 121, BSNS 112
- Restriction
- COMP 120, STAT 260
- Schedule C
- Arts and Music, Science
- Contact
- Teaching staff
To be advised.
- Textbooks
To be confirmed.
- Graduate Attributes Emphasised
- Lifelong learning, Scholarship, Communication, Critical thinking, Information literacy.
View more information about Otago's graduate attributes. - Learning Outcomes
Students who successfully complete this paper will be able to
- Use R programming syntax and control flow
- Investigate, tidy, subset, recode and combine data sets
- Create, interpret and critique graphical summaries of data
- Use numerically intensive approaches to fit and assess basic models
- Create online tools to share data and model output