After successful completion of the course, students are able to apply the methods learned in the lecture (142.340) to simulated and real data sets and to analyze the results with repsect to their quality and significance.
Descriptive statistics; elementary introduction to probability; discrete and continuous random variables and their properties; estimation of unknown parameters from random samples; confidence intervals; statistical testing of hypotheses; introduction into Bayesian statistics; testing of hypotheses; linear models and regression.
Solution of problems on the blackboard and by programs. Python preferred, but not obligatory.
The course starts on October 8, 2019 and ends on December 10,2019. Attendance of course 142.340 is required.
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Registration via TISS, attendance of course 142.340 is required.
Application is currently locked manually.
For literature and course material see 142.340
Mathematics of the first two semesters.