Undergraduate Course: Probability (MATH08066)
Course Outline
| School | School of Mathematics |
College | College of Science and Engineering |
| Course type | Standard |
Availability | Available to all students |
| Credit level (Normal year taken) | SCQF Level 8 (Year 2 Undergraduate) |
Credits | 10 |
| Home subject area | Mathematics |
Other subject area | None |
| Course website |
None |
Taught in Gaelic? | No |
| Course description | 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. |
Information for Visiting Students
| Pre-requisites | None |
| Displayed in Visiting Students Prospectus? | No |
Course Delivery Information
|
| Delivery period: 2013/14 Semester 1, Available to all students (SV1)
|
Learn enabled: Yes |
Quota: None |
Web Timetable |
Web Timetable |
| Course Start Date |
17/09/2013 |
| Breakdown of 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 Notes |
Students must pass exam and course overall.
|
| Breakdown of Assessment Methods (Further Info) |
Written Exam
85 %,
Coursework
15 %,
Practical Exam
0 %
|
| Exam Information |
| Exam Diet |
Paper Name |
Hours:Minutes |
|
|
| Main Exam Diet S1 (December) | MATH08066 Probability | 2:00 | | |
Summary of Intended Learning Outcomes
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. |
Assessment Information
| See 'Breakdown of Assessment Methods' and 'Additional Notes' above. |
Special Arrangements
| None |
Additional Information
| Academic description |
Not entered |
| Syllabus |
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)
|
| Transferable skills |
Not entered |
| Reading list |
A First Course in Probability (8th Editions), Sheldon Ross, |
| Study Abroad |
Not entered |
| Study Pattern |
Not entered |
| Keywords | Prob |
Contacts
| Course organiser | Dr Tibor Antal
Tel: (0131 6)51 7672
Email: Tibor.Antal@ed.ac.uk |
Course secretary | Mr Martin Delaney
Tel: (0131 6)50 6427
Email: Martin.Delaney@ed.ac.uk |
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© Copyright 2013 The University of Edinburgh - 10 October 2013 4:51 am
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