23310a
Lecture
WiSe 23/24: V Einführung in R für statistische Anwendungen
Felix May, Jonas Vollhüter, Felix Nößler
Information for students
additional information: Modulbeschreibung Einführung in R für statistische Anwendungen close
Additional information / Pre-requisites
Please work on a computer, R is difficult to install on a tablet
Comments
Content:
Vorlesung: Lectures cover specific introductory topics in statistics and coding in the script language R. These are mainly:
Qualification objectives:
Students are familiar with programming methods in the script language R. They can create data tables, read data, and manage data sets in R. They can apply visualization techniques for data. They have a detailed knowledge of basic statistical methods such as Linear Models and Generalized Linear Models. You will be able to select useful statistical methods for a given data set, perform analyses in R independently, and interpret the results correctly. You will be able to present statistical methods and results in oral and written form to a professional audience. close
Vorlesung: Lectures cover specific introductory topics in statistics and coding in the script language R. These are mainly:
- Creating data tables
- Coding basics
- Syntax in R
- Visualization of data, creating figures on publication level
- Basic statistics
- Linear models (Regression, ANOVA; ANCOVA)
- Normality tests and method selection
- Interpretation of ANOVA tables
- Generalized Linear Models for non-normal distributed data
- Description of methods and presentation of results
Qualification objectives:
Students are familiar with programming methods in the script language R. They can create data tables, read data, and manage data sets in R. They can apply visualization techniques for data. They have a detailed knowledge of basic statistical methods such as Linear Models and Generalized Linear Models. You will be able to select useful statistical methods for a given data set, perform analyses in R independently, and interpret the results correctly. You will be able to present statistical methods and results in oral and written form to a professional audience. close