Course Content (Syllabus)
PROBABILITY THEORY:
Probability space, conditional probability, total probability, Bayes’ theorem. Random variables. Distribution functions of discrete and continuous random variables. Theoretical distributions (binomial, geometric, negative geometric, hypergeometric, Poisson, uniform, normal, exponential). Characteristics and parameters of distributions (mean value, variance, other moments, mode, Tchebycheff inequality). Functions of random variables.
STATISTICS:
Descriptive statistics of data (summary statistics and graphs). Estimation of distribution parameters from observations of a random variable, properties of estimators, the method of moments and the method of maximum likelihood, estimation of confidence interval for the mean, variance and difference of two means. Regression and correlation analysis, simple linear regression.