Probability, random variable, density function, random vector, function of random variable. Random sampling, point and interval estimates, testing of parametric and nonparametric hypotheses, linear and nonlinear regression, ANOVA.
Abstract:
Definition of probability, random variable and its description, known distributions, random vector, function of random variable. Methods of point estimation. Testing of statistical hypothesis. Regression and correlation, linear regression, correlation coefficient, coefficient of determination, the general linear model, statistical inference in linear regression, analysis of variance, multiple regression, the use of matrices in regression.
Objectives:
To improve student's knowledge of probability and to teach and exercise students the basis algorithms for static data analysis.