Statistical analysis methods with R
Target group: all scientists
The conditions of participation are based on the current rules for face-to-face events at the time of the event.
Graduate and doctoral students are often faced with the challenge of having to collect and analyse their own data in dissertations, projects and seminars. In order to acquire the necessary skills, this course will provide an insight into basic and advanced statistical analysis methods. The focus is on methods of market research and psychometrics. For this purpose, the procedures listed below will be discussed in their approach and applied with sample data sets using the free statistical software R.
- Data preparation in R
- contingency analysis and chi-square test
- t-test and other mean comparisons
- Linear models such as regression and analysis of variance
- Factor and reliability analysis
- (covariance-based) structural equation models
- Participants* are expected to have prior knowledge of statistics (distributions, estimation, testing) and the specified statistical procedures (at least correlation, t-test, regression).
- Your own notebook with Windows, MacOS or Linux derivatives and sufficient user rights to install programs (please do not forget a power supply).
- Software R and RStudio