Probability I (MATH11711)

The details given may be subject to change, and should be used for informational purposes only. Course Unit details can change regularly, and those given will be applicable from the current point in time, unless otherwise stated.
Credit rating
10
Unit level
Level 1
Teaching period(s)
Semester 1
Academic career
Undergraduate
Offered by


Available as a free choice unit?
No

Course unit overview

This unit introduces the basic ideas and techniques of probability, including the handling of random variables and standard probability distributions and the crucial notions of conditional probability and of independence, to equip the students with the necessary knowledge required for probability related courses in their later studies

Teaching staff

Teaching staff Course Unit Role
Peter Johnson Unit coordinator
Thomas Bernhardt Unit coordinator

Aims

The unit aims to introduce the basic ideas and techniques of probability, including the handing of random variables and standard probability distributions and the crucial notions of conditional probability and of independence, to equip the students with the necessary knowledge required for probability related courses in their later studies.  

Learning outcomes

On the successful completion of the course, students will be able to: 
1. describe how mathematics models randomness and model real-world situations involving randomness 
2. compute probabilities and expectations using various formulas and demonstrate why those formulas hold
3. describe standard distributions and apply them in the context of a sequence of biased coin flips, exponential waiting times, or the sum of independent random variables
4. explain and appraise statements that hold for a large class of distributions like the Central Limit Theorem, or the law of large numbers
 

Employability skills

Syllabus

The course gives a general introduction to probability theory and is a prerequisite for all future probability and statistics courses.

1. Probability space: sample space and counting principles; events and probability. 
2. Conditional probability and independence. 
3. Discrete and continuous random variables; (joint) distributions. 
4. Expectation and variance of a random variable. 
5. Classical distributions including the Binomial, Geometric, Poisson, Normal and Exponential distributions. 
6. Probability theory: The Central Limit Theorem. Law of Large Numbers. 

Assessment methods

Written exam 70%
Other 30%

Feedback methods

There are supervisions in alternate weeks which provide an opportunity for students' work to be marked and discussed and to provide feedback on their understanding. Coursework or in-class tests (where applicable) also provide an opportunity for students to receive feedback. Students can also get feedback on their understanding directly from the lecturer, for example during the lecturer's office hour

Recommended reading

1) S. Ross, A First Course in Probability, Macmillan.

2) D. Stirzaker, Elementary Probability, Cambridge University Press. Available electronically through the library.

3) HELM consortium, HELM Workbooks 35, 37, 38 and 39, Open Access Publication. Available electronically on the internet.

Study hours

Scheduled activity hours
Lectures 22
Tutorials 5
Placement hours
0
Independent study hours 73

Pre/co-requisites

Unit Code Title Type Required?

Additional notes

Attachments

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