Subsections
[Cr:3, Lc:2, Tt:1, Lb:0]
- Recapitulation: Counting (urn, coins, cards).
- Axiomatic approach to probability, conditional probability,
independence of events.
- Discrete random variables, probability mass function, some standard
discrete distributions and examples.
- Continuous random variables, probability density function, some
standard continuous distributions and examples.
- Bivariate distributions (discrete and continuous), marginal and
conditional distributions, covariance, correlation coefficient.
- Moments, Markov's inequality, Chebychev's inequality.
- Sums of independent random variables, law of large numbers, central
limit theorem
- A glimpse into estimation theory (maximum likelihood estimation,
method of moments) and testing of hypothesis.
- K. L. Chung and F. AitSahila, Elementary Probability Theory,
Springer (2004).
- R. Isaac, The Pleasures of Probability, Springer (Undergraduate
Texts in Mathematics) (1995).
- S. Ross, A First Course in Probability, Pearson Education Inc.
(2006).
