Statistics

- Introduction to descriptive statistics and basic terminology (means, spread, distribution, index, correlation, linear regression); - conditional probability; discrete random variable and distribution; continuous random variable and normal distribution; - inductive statistics (basics; test theory; tests in the context of various models; classic linear regression model, simple and multiple regression)

Mode of delivery

face to face

Type

compulsory

Recommended or required reading and other learning resources/tools

Alt: Statistik. Wien: Linde (current edition)

Planned learning activities and teaching methods

Integrated course: lecture, case studies, discussion

Assessment methods and criteria

Assessment is based on the final exam as well as on the quality of students' assignments, presentations etc.

Prerequisites and co-requisites

Module Civil Law and Mathematics

Infos

Degree programme

Project Management & IT (Bachelor)

Cycle

Bachelor

ECTS Credits

3.00

Language of instruction

German

Curriculum

Full-Time

Academic year

2023

Semester

2 SS

Incoming

Yes

Learning outcome

Upon successful completion, students will have acquired basic knowledge of statistical concepts and they will be able to apply them to diverse economic problems. Students will be able to explain and use basic analytical methods of descriptive statistics as well as the most important probability laws and relevant distribution laws. They will be able to calculate parameter estimates, test hypotheses and transfer a sample survey to the corresponding universe. They will be able to quantitatively analyse univariate and multivariate data sets.

Course code

0387-17-01-VZ-DE-19