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R: Crash Course in Statistics
In this course you will get an introduction to inferential statistics (hypothesis testing), which is the basis for statistical tests and models. This is followed by (selected) statistical tests and models, which are introduced in an application-oriented way and executed with R/RStudio.
The course half days are arranged in such a way that I present my course notes at the beginning. Afterwards you will work on practices individually or in small groups to intensify the topics.
I am going to support you during the work on the practices and there will be available suggested solutions of the practices.
Depending on the topic, the level of the course is in the range of outcome levels for a statistics master module of universities of applied sciences or above, and in the range of outcome levels for a statistics master module of universities.
General information
| Duration | 14 hours |
|---|
- Sampling: A brief overview
- Inferential statistics (theory)
- Sampling Distribution
- Confidence Interval
- Hypothesis testing (example: z test)
- Selected statistical tests and models (application with R)
- t test
- One-factor and two-factor analysis of variance
- Chi-square test
- Linear regression analysis
- Non-parametric tests
Course:
- ARE - R: Basic Introduction
Dates