This course is an introduction to probability and statistic for students in statistics, applied mathematics, electrical engineering and computer science. This core course is intended to provide a solid general background in probability and statistics that will form the basis of more advanced courses in statistics. Content: (1) – Probability: Axioms of probability, Conditional probability and independence, Conditional probability and independence, Random variables, expectation, and moments, discrete random variables, Continuous random variables, Pairs of random variables, Limit theorems. (2) – Theory of Statistics: Estimators and properties, Optimality, Maximum likelihood, HypoThesis tests, Confidence intervals, Bayesian statistics. (3) – Methods of Statistics: Graphics and exploratory data analysis, Simple/multiple regression and least squares, Logistic regression, Analysis of variance, Robust and nonparametric statistics.