MAS1608 : Introduction to Probability & R
- Offered for Year: 2020/21
- Module Leader(s): Dr Tom Nye
- Lecturer: Dr Sarah Heaps
- Owning School: Mathematics, Statistics and Physics
- Teaching Location: Newcastle City Campus
Semesters
| Semester 2 Credit Value: | 20 |
| ECTS Credits: | 10.0 |
Aims
To develop ideas and methods that are essential for the study of probability and statistics. To develop a familiarity with ideas of discrete and continuous probability models and their interpretation. To develop concepts in probability that underpin methods of statistical inference.
Module summary
The course will cover the key concepts required for further study of probability and statistics. We begin with the fundamentals of probability theory, considering probability for discrete outcomes such as National Lottery draws or poker hands. We will then move on to probability distributions and investigate how they can be used to model uncertain quantities such as the response of patients to a new treatment in a clinical trial and the occurrence of earthquakes in tectonically active regions. The module will introduce ideas of bivariate distribution and covariation, which are fundamental to many of the most useful statistical techniques.
Outline Of Syllabus
Introduction to random variation and probability including the probability axioms.
Conditional probability and independence.
Discrete probability models: the binomial, geometric and Poisson distributions. Discrete bivariate models.
Continuous probability models: the uniform, exponential and Normal distributions.
QQ-plot for Normal case. Bivariate continuous distributions.
Use of R for mathematical computing. Getting started, input and output, data types, plotting and simple calculations, control statements, functions, random variables. Use of R for illustration of fundamental concepts in probability.
Teaching Methods
Please note that module leaders are reviewing the module teaching and assessment methods for Semester 2 modules, in light of the Covid-19 restrictions. There may also be a few further changes to Semester 1 modules. Final information will be available by the end of August 2020 in for Semester 1 modules and the end of October 2020 for Semester 2 modules.
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Scheduled Learning And Teaching Activities | Lecture | 9 | 1:00 | 9:00 | Synchronous On Line Material |
| Structured Guided Learning | Lecture materials | 36 | 1:00 | 36:00 | Non-Synchronous Activities |
| Guided Independent Study | Assessment preparation and completion | 30 | 1:00 | 30:00 | Completion of In Course Assessment |
| Scheduled Learning And Teaching Activities | Small group teaching | 9 | 1:00 | 9:00 | Present in Person |
| Structured Guided Learning | Structured non-synchronous discussion | 18 | 1:00 | 18:00 | Non Synchronous Discussion to Support Learning |
| Scheduled Learning And Teaching Activities | Drop-in/surgery | 4 | 1:00 | 4:00 | Office Hour or Discussion Board Activity |
| Guided Independent Study | Independent study | 94 | 1:00 | 94:00 | Preparation Time for Lectures, Background Reading, Coursework Review |
| Total | 200:00 |
Teaching Rationale And Relationship
Non-synchronous online materials are used for the delivery of theory and explanation of methods, illustrated with examples, and for giving general feedback on assessed work. Present-in-person and synchronous online sessions are used to help develop the students’ abilities at applying the theory to solving problems and to identify and resolve specific queries raised by students, and to allow students to receive individual feedback on marked work. Students who cannot attend a present-in-person session will be provided with an alternative activity allowing them to access the learning outcomes of that session. In addition, office hours/discussion board activity will provide an opportunity for more direct contact between individual students and the lecturer: a typical student might spend a total of one or two hours over the course of the module, either individually or as part of a group.
Student should consult their individual timetable for up-to-date delivery information.
Assessment Methods
Please note that module leaders are reviewing the module teaching and assessment methods for Semester 2 modules, in light of the Covid-19 restrictions. There may also be a few further changes to Semester 1 modules. Final information will be available by the end of August 2020 in for Semester 1 modules and the end of October 2020 for Semester 2 modules.
The format of resits will be determined by the Board of Examiners
Exams
| Description | Length | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|---|
| Written Examination | 120 | 2 | A | 60 | In Class Test |
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Written exercise | 2 | M | 20 | N/A |
| Written exercise | 2 | M | 20 | N/A |
Assessment Rationale And Relationship
The course assessments 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/
- MAS1608's Timetable