MAS2906 : Computational Probability and Statistics with R
- Offered for Year: 2022/23
- Module Leader(s): Dr Lee Fawcett
- Owning School: Mathematics, Statistics and Physics
- Teaching Location: Newcastle City Campus
Semesters
| Semester 1 Credit Value: | 10 |
| ECTS Credits: | 5.0 |
Aims
To introduce and reinforce a range of concepts in probability and statistics with particular emphasis on illustrations in R, including methods that will be useful towards future project work. To reinforce the computing in R studied within MAS1608, and to move towards expectations of more independent programming.
Module summary
Computational methods are of great use in a wide range of applications of probability and statistics. This module builds on the probability and the use of R introduced at Stage 1. Students will be introduced to additional concepts and techniques, some of increasing mathematical and computational sophistication. In implementing these methods, students will attain a deeper understanding of foundational probability and statistics, increasing competence with mathematical/statistical computing, and an increasing ability to use such methods independently, towards project-orientated goals.
Outline Of Syllabus
Review of basic ideas in R: Vector and dataframe subsetting and manipulation, data summaries, functions and control statements. Review of probability ideas: illustrations of properties of univariate, bivariate and trivariate distributions in R, including use of conditional distributions. Transformations of random variables, with illustrations in R. Sampling distributions. Illustration of properties of hypothesis tests and confidence intervals.
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Guided Independent Study | Assessment preparation and completion | 47 | 1:00 | 47:00 | Preparation time for lectures, background reading, coursework review |
| Scheduled Learning And Teaching Activities | Lecture | 11 | 1:00 | 11:00 | Formal Lectures – Present in Person |
| Scheduled Learning And Teaching Activities | Practical | 11 | 1:00 | 11:00 | Computer Practicals – Present in Person |
| Scheduled Learning And Teaching Activities | Practical | 11 | 1:00 | 11:00 | Problem Classes – Synchronous On-Line |
| Scheduled Learning And Teaching Activities | Drop-in/surgery | 5 | 1:00 | 5:00 | Synchronous On-Line |
| Guided Independent Study | Independent study | 15 | 1:00 | 15:00 | Completion of in course assessments |
| Total | 100:00 |
Teaching Rationale And Relationship
Practicals are used for the delivery of theory and explanation of methods, illustrated with examples, and for giving general feedback on marked work. Problem Classes are used to help develop the students’ abilities at applying the theory to solving problems.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Exams
| Description | Length | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|---|
| Written Examination | 120 | 1 | A | 50 | Off-campus test |
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Prob solv exercises | 1 | M | 25 | Problem-solving exercises |
| Prob solv exercises | 1 | M | 25 | Problem-solving exercises |
Assessment Rationale And Relationship
A substantial class test is appropriate for the assessment of the material in this module. The coursework assignments allow the students to develop their problem solving techniques, to practise the methods learnt in the module, to assess their progress and to receive feedback; these assessments have a secondary formative purpose as well as their primary summative purpose.
Reading Lists
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- MAS2906's Timetable