**[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).