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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2017/2018

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DRPS : Course Catalogue : School of Mathematics : Mathematics

Undergraduate Course: Probability (MATH08066)

Course Outline
SchoolSchool of Mathematics CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 8 (Year 2 Undergraduate) AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryA first course in Probability, assuming prior knowledge of calculus, basic
combinatorics and set theory.
Course description Probability theory, the mathematical description of chance, is a subject in its own right but also
the bedrock on which Statistics and Data Science are built. We are surrounded by important
questions involving chance but our intuition on the subject is often wrong. This course aims to give
an understanding of the subject that will help you understand issues where chance plays a central
role as well as preparing you for further study.

The course covers fundamental concepts and basic examples, assuming no previous knowledge of
the subject. Some knowledge of calculus and basic combinatorics and set theory is assumed.

The central topics will include:

- Fundamentals of mathematical probability: sample spaces; events; independence; conditional probability and Bayes¿s Theorem. Discrete and continuous distributions.
- Random variables: expectation; variance; sums and products.
- Fundamental distributions: uniform; normal; binomial, Poisson, exponential and their
application.
- The idea and applications of the central limit theorem.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed: ( Introduction to Linear Algebra (MATH08057) AND Calculus and its Applications (MATH08058)) OR Accelerated Algebra and Calculus for Direct Entry (MATH08062)
Co-requisites
Prohibited Combinations Students MUST NOT also be taking Probability with Applications (MATH08067)
Other requirements None
Information for Visiting Students
Pre-requisitesVisiting students are advised to check that they have studied the material covered in the syllabus of each pre-requisite course before enrolling.
High Demand Course? Yes
Course Delivery Information
Academic year 2017/18, Available to all students (SV1) Quota:  None
Course Start Semester 1
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 22, Seminar/Tutorial Hours 5, Summative Assessment Hours 2, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 69 )
Additional Information (Learning and Teaching) Students must pass exam and course overall.
Assessment (Further Info) Written Exam 80 %, Coursework 20 %, Practical Exam 0 %
Additional Information (Assessment) Coursework 20%, Examination 80%
Feedback Not entered
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S1 (December)MATH08066 Probability2:00
Resit Exam Diet (August)(MATH08066) Probability2:00
Learning Outcomes
On completion of this course, the student will be able to:
  1. demonstrate a conceptual understanding of fundamental concepts of probability and be able to derive basic results from them.
  2. carry out practical computations with standard concepts (such as conditional probabilities, expectations, variances) and standard distributions covered in the course.
  3. model situations with an appropriate distribution and relate the properties and outcomes of the model to the original situation.
  4. explain their reasoning about probability clearly and precisely, using appropriate technical language.
Reading List
Notes and direction to particular online resources will be provided. There are
numerous books and other online resources on basic probability. One book that would be an appropriate alternative source is ¿A First Course in Probability¿ by Sheldon Ross.
Additional Information
Graduate Attributes and Skills Not entered
KeywordsProb
Contacts
Course organiserDr Toby Bailey
Tel: (0131 6)50 5068
Email: t.n.bailey@ed.ac.uk
Course secretaryMr Martin Delaney
Tel: (0131 6)50 6427
Email: Martin.Delaney@ed.ac.uk
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