MATH6166 Statistical Computing for Data Scientists
Module Overview
This module will provide an introduction to basic statistical programming in R. It consists of lecturers and associated practical sessions for students to gain hands-on experience of statistical programming.
Aims and Objectives
Learning Outcomes
Learning Outcomes
Having successfully completed this module you will be able to:
- Students should be able to enter, import and manipulate data.
- Students should be able to produce basic graphics.
- Students should be able to write functions, loops and code for conditional execution.
Syllabus
- R syntax - Importing data - Data manipulation - Graphics - Writing functions - Loops and conditional execution
Learning and Teaching
Teaching and learning methods
18 sessions, in combination of lectures and computer labs, (this may all be delivered online)
| Type | Hours |
|---|---|
| Teaching | 18 |
| Independent Study | 57 |
| Total study time | 75 |
Resources & Reading list
Garrett Grolemund and Hadley Wickham. R for Data Science.
Assessment
Summative
| Method | Percentage contribution |
|---|---|
| Coursework | 100% |
Referral
| Method | Percentage contribution |
|---|---|
| Coursework | 100% |
Repeat Information
Repeat type: Internal & External
Costs
Costs associated with this module
Students are responsible for meeting the cost of essential textbooks, and of producing such essays, assignments, laboratory reports and dissertations as are required to fulfil the academic requirements for each programme of study.
In addition to this, students registered for this module typically also have to pay for:
Books and Stationery equipment
Recommended texts for this module may be available in limited supply in the University Library and students may wish to purchase reading texts as appropriate.
Please also ensure you read the section on additional costs in the University’s Fees, Charges and Expenses Regulations in the University Calendar available at www.calendar.soton.ac.uk.