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 where to find the specific outputs. 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
Please note that this course is primarily a programming course and we will not devote any time towards explaining how different statistical methods work or how to interpret their results. Instead, the focus of this course will be on how to write code in R that implements various statistical methods. In addition to some knowledge of programming R, we expect participants to have a basic understanding of the theory behind hypothesis testing and regression analysis. For participants who are interested in building an understanding of the theory behind different statistical methods and the interpretation of their results, we recommend registering for our Introduction to Statistics course instead.
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.
Target audience:
People who are very familiar with statistical methods concepts such as hypothesis testing and linear regression and have experience conducting statistical analysis using a programming language or software other than R (for e.g. Python, SAS, SPSS, GraphPad Prism) and now want to know how to implement classical statistical methods in R. The participants are also expected to have a familiarity with basic commands in R (such as loading data sets etc.) that are covered in the course Introduction to R.
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: