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 prerequisites. 
Information for Visiting Students
Prerequisites  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 2state discretetime 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. 1.12.3 of Sheldon Ross.)
Week 2: Samples spaces with equally likely outcomes. (Ch. 2.42.5)
Week 3: Conditional Probability, Bayes's formula (Ch 3.13.3)
Week 4: Independence (Ch 3.43.5)
Week 5: Discrete random variables, expectation, variance (4.14.5),
Week 6: Bernoulli, binomial, Poisson, geometric, negative binomial RVs (4.64.9)
Week 7: Sums of RV's, hypergeometric RV, Continuous RVs (4.95.3)
Week 8: Uniform, normal, exponential, gamma RVs (5.45.6)
Week 9: Joint and independent RVs (6.16.2)
Week 10: Sums of independent RVs, Limit theorems: Markov, Chebyshev, weak law of large numbers, Moment generating function (6.38.2)
Week 11: Central limit theorem, Poisson Process, Overview (8.39.1)

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 

