continuous random variables, expectation and variance
Course Material
- Finite probability spaces: Basic concept
- probability and related frequency
- combination of events, examples
- independence, random variables
- expected value, standard deviation
- Chebyshev's inequality, independence of random variables
- multiplicatively of the expected value
- additivity of the variance, discrete probability distribution
- Probability as a continuous set function: Sigma-algebras, examples
- Mid Term Exam
- continuous random variables, expectation and variance
- normal random variables
- continuous probability distribution
- Applications: De Moivre-Laplace limit theorem
- weak and strong law of large numbers
- the central limit theorem
- Winter vacations Markov chains continuous Markov process
- Final Term Exam
- Chapters 18
- Department Mathematics(SCB)
- Teacher
Mr. Muhammad Shakeel Nawaz
