Probability and Statistics

Dr. Anat Sakov

1. Probability space. Conditional probability and Bayes rule. Independence .
2. Discrete random variables. Binomial, geometric and Poisson distributions. Poisson process.
3. Continuous random variables. Exponential and normal distributions.
4. Expectation and variance.
5. Two-dimensional random variables. Correlation and covariance.
6. Central limit theorem and law of large numbers.
7. Principals in estimation. Maximum likelihood estimation and method of least squares.
8. Principals of confidence intervals and statistical testing. Goodness of fit test.