PROBABILITY (MA3005)

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Examines probability in its various components and through its diverse applications. Topics include: combinatorial analysis, axioms of probability, discrete random variables and distributions & continuous random variables and probability density functions, joint distribution functions, law of large numbers. The statistical concepts of conditioning, independence and expectation will be highlighted, as well as the notion of moments. Selected applications will shed light on the use of probability in various fields.

Code: 
MA3005
Name: 
PROBABILITY
Discipline: 
MA (Mathematics)
Type: 
Regular
Level: 
Undergraduate
Credits: 
4
Can be taken twice for credit?: 
No
Pre-requisites: 
MA1030CCM
Co-requisites: 
None

Learning Outcomes

  1. Extend this knowledge to joint (continuous and discrete) distribution functions and solve related problems.
  2. Have knowledge of the distinctive characteristics of the continuous and discrete distributions studied (Normal, Exponential, Uniform, Gamma // Binomial, Negative Binomial, Hypergeometric, Poisson, Geometric) and acquire the ability to handle connected applications appropriately.
  3. Understand the importance of the concepts of independence, conditioning and moment in probability theory.
  4. Understand the relevance of combinatorics in highlighting probability features.

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