Descriptive statistics. Concept, rules and properties of probability. Conditional probability, independence of events, Bayes theorem. Distributions of random variables. Expected value and variance. Basic distributions and applications. Bivariate distributions, independence of random variables. Central limit theorem. Sampling distributions. Point estimation, confidence intervals and statistical hypothesis testing. Linear model: estimation and testing of parameters, coefficient of determination, prediction. Χ2 – goodness of fit test, probability plotting. Contingency tables. Applications using computer packages. Introduction to adjustment theory, principle of Least Squares. Estimation of a single variable from direct measurements (equally and unequally weighted). Multidimensional variables. Variance-Covariance propagation. Bivariate normal distribution, error ellipse. Least Squares adjustments by the methods of observation and condition equations. Estimation of Variance-Covariance matrices. Geodetic applications.
