Descriptive Statistics, Probability: definitions and axioms, conditional probability, independent events, law of total probability, Bayes’ theorem, combinatorics.
Random variables: basic discrete and continuous univariate distributions, exponential family of distributions, mean and variance of random variables.
Multivariate distributions: marginal distributions, independence of random variables.
Central limit theorem.
Estimation: method of maximum likelihood, moment estimators. Applications.
Confidence intervals: for the mean and variance of one population, for the difference of the means of two populations, for the ratio of the variances of two populations. Approximate confidence intervals.
Hypothesis testing: for the mean and variance of one population, inference for two populations. X^2 tests.
Correlation. Simple linear regression, introduction to the linear model.Multiple linear regression. Estimation of parameters and properties of the estimators. Applications.
- Teacher: Φιλία Βόντα
ECTS : 5
Language : el
Learning Outcomes : Upon successful completion of the course, the student acquires the following skills: • they will be able to solve problems in the field of Probabilities • they will be able to analyze data • use statistical techniques to draw useful conclusions for a given population based on a sample from that population • apply general statistical methods to data from the science of Surveying Engineers. Upon successful completion of the course, the student acquires the following abilities: • Search, analyze and synthesize data and information, using the necessary technologies • Decision making • Autonomous work • Teamwork Search, analysis and synthesis of data and information, using the necessary technologies Decision making Autonomous work Teamwork Work in an international environment Work in an interdisciplinary environment.