Statistics Fundamentals

The concepts taught in statistics make it possible to analyze data material, e.g. as it occurs in measurements. In probability theory, the most important distributions are introduced in order to be able to make statements about random processes. With the help of various estimation functions, it is possible to test assumptions about a population on the basis of sample data.

• Descriptive statistics
• Elementary probability theory
• Conditional probability
• Discrete and continuous distribution functions
• Estimation of parameters
• Testing hypotheses
• Regression and correlation

• Students can analyse and visualize data sets using the most important statistical parameters.
• Students know the axiomatic structure of probability theory and can use counting techniques and relative frequencies to determine the probabilities of events in a random experiment.
• Students know the principle of random variables and can use this for modeling. They know the concept of expected value and variance and can calculate and interpret these. They know the most important distributions and know which processes can be modeled with them.
• Students can make statements about the parameters of the population based on samples. They can determine confidence intervals for parameter estimates and assess their significance.
• Students can formulate hypotheses about the population in such a way that they can be tested with sample data. Students know important statistical test procedures and can apply them.
• Students can use correlation and regression analysis to investigate and describe the relationship between two variables.
• Students can implement the methods covered using a tool (Excel).