Undergraduate Course: Probability (MATH08066)
|School||School of Mathematics
||College||College of Science and Engineering
|Credit level (Normal year taken)||SCQF Level 8 (Year 2 Undergraduate)
||Availability||Available to all students
|Summary||An introduction to probability; no prior knowledge is required.
Week 1: Introduction, counting, foundations of Probability: sample spaces and events (Chap. 1.1-2.3 of Sheldon Ross.)
Week 2: Samples spaces with equally likely outcomes. (Ch. 2.4-2.5)
Week 3: Conditional Probability, Bayes's formula (Ch 3.1-3.3)
Week 4: Independence (Ch 3.4-3.5)
Week 5: Discrete random variables, expectation, variance (4.1-4.5),
Week 6: Bernoulli, binomial, Poisson, geometric, negative binomial RVs (4.6-4.9)
Week 7: Sums of RV's, hypergeometric RV, Continuous RVs (4.9-5.3)
Week 8: Uniform, normal, exponential, gamma RVs (5.4-5.6)
Week 9: Joint and independent RVs (6.1-6.2)
Week 10: Sums of independent RVs, Limit theorems: Markov, Chebyshev, weak law of large numbers, Moment generating function (6.3-8.2)
Week 11: Central limit theorem, Poisson Process, Overview (8.3-9.1)
Information for Visiting Students
|Pre-requisites||Visiting 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?
Course Delivery Information
|Academic year 2016/17, Available to all students (SV1)
|Learning and Teaching activities (Further Info)
Lecture Hours 22,
Seminar/Tutorial Hours 5,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
|Additional Information (Learning and Teaching)
Students must pass exam and course overall.
|Assessment (Further Info)
|Additional Information (Assessment)
||Coursework 15%, Examination 85%
||Hours & Minutes
|Main Exam Diet S1 (December)||MATH08066 Probability||2:00|
|Resit Exam Diet (August)||(MATH08066) Probability||2:00|
On completion of this course, the student will be able to:
- To understand the basic notions of probability, conditional probability and independence..
- To be familiar with the geometric, bionomial and Poisson discrete distributions.
- To be familiar with the uniform, exponential and normal continuous distributions.
- To be able to work with several random variables and functions of them.
- To understand the basic limit theorems of probability.
|A First Course in Probability (8th Editions), Sheldon Ross,|
|Graduate Attributes and Skills
|Course organiser||Dr Tibor Antal
Tel: (0131 6)51 7672
|Course secretary||Mr Martin Delaney
Tel: (0131 6)50 6427
© Copyright 2016 The University of Edinburgh - 3 February 2017 4:41 am