Lecture Session1 : Probability concepts, Types of Events, Axioms and theorems
Lecture Session2 : Conditional probability, Baye’s theorem – without proof, Applications- Baye’s Theorem
Lecture Session 3 : Random variables – Discrete case, Probability Mass function
Tutorial Session 4 : Problem solving using tutorial sheet 1
Lecture Session 5 : Cumulative distribution function, Mathematical expectation –discrete case
Lecture Session 6 : Variance, Probability density function
Lecture Session 7 : Cumulative distribution function, Mathematical expectation-continuous case
Tutorial Session 8 : Problem solving using tutorial sheet 2
Lecture Session 9 : Variance, Raw Moments
Lecture Session 10 : Central Moments, Moment generating function,
Lecture Session 11 : MGF- discrete random variable, continuous random variable
Tutorial Session 12 : Problem solving using tutorial sheet 3, Applications of Probability and Random variables in Engineering field