Statistical models with R
Course description
Requirements:
Basic skills in programming with R (can be obtained in the Introduction to R course).
Knowledge in statistics especially hypothesis testing and linear regression.
Course overview:
The introductory course describes the application of some basic statistical methods in the statistical software R. Participants will learn how to start applying statistical methods using R and how to interpret the R output. Consider, it is a programming course, and it requires previous knowledge of statistical theory.
Topics:
The course covers the application of the following statistical methods in R:
- Descriptive statistics
- Hypothesis testing
- T-test
- Wilcoxon-test
- ANOVA and pairwise tests
- Linear regression
This is not a classical statistics course, but a programming course. In case you are interested in learning when to apply which method or the relationship between different statistical models, we recommend the course Introduction to Statistics.
Moreover, this is not a beginner’s course in R programming. You are expected to have some basic skills in R (as taught in the Introduction to R course)
A graphical explanation of the differences between the courses is given here.
Methods:
- We first briefly describe the statistical theory behind the methods and their application in R. We then provide hands-on examples with best-practice solutions.
Format:
- Duration: 1 Day
- Language: English
- This course will be offered either on campus (in person), or online.
- For online courses we use the software Zoom.
Dates and Application:
- This course is currently not part of the HR Development program at Helmholtz Munich. Employees of Helmholtz Munich can either participate in the four-day version of this course (Introduction to Statistics), or in the courses we provide via HIDA (see below).
- Courses provided for HIDA: