Hier finden Sie einige Informationen, die Sie gern kopieren und zum Bewerben des Kurses auf Ihrer Internetseite und in Aushängen verwenden können. Wählen Sie die Beschreibung zum von Ihnen gebuchten Kurs (Basic Statistics oder Basic R) aus und nutzen Sie gern meine Trainerbeschreibung unten und das Foto von mir zum Download. Sie können auch den Text komplett als PDF unten downloaden.

Kursbeschreibungen zu den Flipped-Classroom-Kursen auf Englisch

Basic Statistics Course

In this Basic Statistics Course you will learn the basics of statistical data analysis for your research projects. The course is application based and will empower you to improve your study planning and get more confident with your statistical analysis.

It contains the following topics:

• Design of experiments / study design
• Data collection and entry
• Structure of statistical analysis
• Significance tests
• Choosing the appropriate statistical method
• Paired and unpaired data
• Level of measurement / variable type
• Checking of assumptions and normality
• Effect size measures
• Sample size calculation and power analysis

The course is organized with self-learning material (short videos, handout and exercises) and two live and online Q&A sessions. After a short kick-off meeting you watch the videos and do the exercises at your own pace. Within an interval of one week we meet for two Q&A sessions online, where you can ask questions concerning the topics or your own projects.

Basic R Course

In this Basic R Course you will learn to use R and Rstudio for doing statistical analysis. You will get to know the most important statistical methods. You will learn how to choose the right method for different situations and use R and Rstudio for analyzing example data with these methods.

The course will cover the following main topics:

• Introduction to R and Rstudio
• General introduction to statistics
• Descriptive statistics and graphics
• Normal distribution
• Significance tests
• Investigation of dependencies and differences
• Post-Hoc-Tests
• Factorial ANOVAs
• Linear and logistic regression

After the course you will

• have lost the fear of using R,
• have learned the basic function of R,
• know how to import and export raw data in R,
• be able to create a descriptive and graphical overview of a data set,
• be able to choose the appropriate significance test or statistical model for an available data set and research question,
• be able to conduct this analysis in R and interpret the results.

The course is organized with self-learning material (short videos, handout, example data and exercises) and three live and online Q&A sessions. After a short kick-off meeting you watch the videos and do the exercises at your own pace. Within an interval of one week we meet for three Q&A sessions online, where you can ask questions concerning the topics and exercises of the course or your own projects.

Trainerprofil

Daniela Keller has been working as a freelance statistical consultant for over ten years. Her greatest passion is to enable students and researchers to use statistics to advance their own research projects. In her career, she experienced that everybody can learn statistics and even can have fun while applying it. She will support you with application-based content and helpful tips to become more competent with statistics and to complete your project successfully.