Three credit hours (3h lecture) Basic concepts of probability, rules of probability, conditional probability, independence, conditional probability and Bayes theorem. Random variables: introduction, discrete and continuous, probability mass and density functions, cumulative distribution function. Common discrete and continuous distributions. Descriptive Statistics: describing and summarizing data sets, histogram, statistical distributions, and inferential statistics: hypothesis testing, significance levels. Correlation, simple linear and multiple regressions. Goodness of fit tests.