NWNR100398 Statistics (AW)

Type
course with continuous assessment
Semester hours
2.5
Lecturer (assistant)
Baumgartner, Vincent Vitez , El-Laban, Josef , Hellmer, Laura , Laa, Ursula , Martinitz, Marie Antonia , Ortega Menjivar, Lena , Spangl, Bernhard
Organisation
Statistics
Offered in
Sommersemester 2026
Languages of instruction
Deutsch
Content

- WH: Descriptive statistics, fundamentals of software (R)
- Probability theory (concept of probability, random variables, distributions, distribution and density functions, quantiles)
- Fundamentals of inferential statistics (parameter estimation, hypothesis testing)
- Selected statistical test procedures for 1- and 2-sample situations
- Analysis of variance (simple, double analysis of variance)
- Regression and correlation analysis (correlation coefficient, simple linear regression)
- Nonparametric methods (Wilcoxon signed-rank test, Wilcoxon rank sum test, Kruskal-Wallis test)
- Contingency tables
Previous knowledge expected

- Basic mathematical knowledge equivalent to an introductory lecture
- Basic data handling and use of the statistical software R (can be learned, for example, in "NWNR100399 Data Science (AW)" or "NWNR001399 First Steps With R")
Objective (expected results of study and acquired competences)

At first the students should realize the uncertainty when describing natural, technical or socio-economical phenomena and methods should be offered to him for modelling (applied probability). The discussed models and methods for describing existing or observed data, for estimating parameters and for testing hypothesis on models and parameters should help the student to handle and analyse data, practical questions and problems in a reasonable statistical way for his own and to judge statistical results in a correct way.
You can find more details like the schedule or information about exams on the course-page in BOKUonline.