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||Students taking this course should have either passed both 'Introduction to Linear Algebra' and 'Calculus and its Applications' or be taking 'Accelerated Algebra and Calculus for Direct Entry' :
A beginning probability course, with no pre-requisites.
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
Course Delivery Information
|Academic year 2014/15, 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|
| 1. To understand the basic notions of Probability
2. To understand conditional probability and independence.
3. To be familiar with the geometric, binomial and Poisson discrete probability densities.
4. To be familiar with the uniform, negative exponential and Normal distributions.
5. To be able to work with some random variables, and calculate their expected values.
6. To be familiar with a 2-state discrete-time Markov chain.
|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 2014 The University of Edinburgh - 12 January 2015 4:21 am