Applied Statistics and Information Processing
Integrated course, 5.00 ECTS
• Descriptive statistics: scales of measurement, empirical distribution, graphic depictions of data, distribution function, ogive, measures of location scales, dispersion measures, skewness and kurtosis, classification of data, concentration, use of statistical software, normal distribution, statistical connections
• Probability theory: Random variables, discrete and common probability distribution, expected value and variance, distribution analysis, test distribution, covariance, multidimensional scattering
• Inferential statistics: Estimation of parameters, Chebychev (Tschebyscheff) theorem, confidence interval incl. its significance in metrology, testing hypotheses incl. key test procedures in sensory science and quality management , Gaussian principle of propagation of uncertainty, basic analysis of variance
Students know the fields of application of statistics and are able to use adequate descriptive and testing methods in the statistical evaluation of data. In addition they are able to asses and critically reflect on the significance of statistical data.
Recommended or required reading and other learning resources / tools
Literature will be announced at the beginning of the course.
Mode of delivery
Prerequisites and co-requisites
Mathematics at Matura level; basic knowledge of IT
Assessment methods and criteria