Course description

Probability of events and definition of probability axioms; Solution of real life examples from civil engineering.
Random Variables : Definition of random variables - discrete and continuous;Probability definitions - PMF, PDF, CDF;Moments and expectations.

Functions of Random Variables : Definition of probability distributions of functions of single random variables - exact methods and approximate methods;Moments and expectations of functions - direct and indirect methods.
Multiple Random Variables : Definition of joint, marginal, and conditional probability distributions;Definitions of moments and expectations, including the definition of correlation coefficient;Functions of multiple random variables.

Common Probability Models : Discrete random variables - binomial distribution, Poissons distribution;
Continuous random variables - exponential distribution, gamma distribution;
Central limit theorem; Normal and lognormal distributions; Extremal distributions.

Statistics and sampling : Goodness of fit tests; regression and correlation analyses; estimation of distribution parameters from statistics;
Hypothesis testing and significance; Bayesian updating of distributions.

What will i learn?