After successful completion of the course, students are able to:

• explain fundamental concepts of statistics
• analyse environmental data with statistical methods and independently process these data,
• develop and implement an algorithm for simple tasks,
• summarise and visualise data,
• apply adequate tests for the statistical evaluation of specific given hypotheses
• use the programming language R
• independently develop, apply and evaluate solutions

Lectures:

1. random variables and distributions
2. estimation
3. hypothesis tests
4. multivariate random variables and methods
5. non-parametric methods
6. experimental design

Exercises:

• R and Rstudio - installation and surface
• R as calculator
• variables (continuous, discrete - binary)
• calculate with variables
• functions
• import data sets
• estimation
• distributions
• visualization
• Implementation and interpretation of statistical analysis in R

• Lectures in presence on the theoretical part
• Introductory presentation in presence of R and Rstudio - installation and surface

• Presentation of the concepts of computer programming and of performing statistical tests using R via deployment of a central web based programming environment (Jupyter notebooks) embedded in the TUWEL course

• support by tutors by lecturers and tutors

• Programming of simple and complex tasks in R (home exercises) with automated evaluation and feedback in Jupyter.

The content of both parts and the detailed organisation of the part dedicated to programming will be explained in the first introductory lecture on 7th March 2023 and will also described in slides available on TUWEL.

The course is held in hybrid mode, consisting of a mix of lectures in presence, programming and submission of homework via Jupyter embedded in TUWEL as well as mandatory handover talks in presence.

If, due to the requirements of the federal government or the TU Wien, it is not possible to hold the course and the examination or parts of the course in attendance, the format will be switched to online. By switching to the online format, the dates announced for the face-to-face course and examination may change. When switching to the online format, the following methods and modes apply:

Method when switching to online format:

Videos (recordings of lectures) and Jupyter/TUWEL for the exercise part

Exam mode when switching to online format:

Written (Zoom Meeting)

Assessment scheme for the online exam:

See “exam modalities”; no change by switching to online format

Required technical equipment for participation in the course and examination:

Device with internet access (notebook, PC, tablet, smartphone)

Certificate of achievement:

See “exam modalities”; no change by switching to online format

Examination modalities are based on tests and submitted programme codes.
Both the exam on the lecture part as well as the exercises have to be positive in order to successfully complete the course.

The exam part consisting of exercises in R must be succesfully completed within the course and must be positive in order to access to the written exam on the lectures.

W. Gurker: Introduction to Mathematical Statistics using R, TU-Verlag, Wien.

Mathematics 1 and 2