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.

Allgemeine Informationen

Dauer 14 hours
  1. Sampling: A brief overview
  2. Inferential statistics (theory)
  • Sampling Distribution
  • Confidence Interval
  • Hypothesis testing (example: z test)
  1. 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
Basic knowledge of statistics and basic knowledge of R.
  • ARE - R: Basic Introduction
The course is aimed at students, doctoral students, and employees of the University of Zurich with basic knowledge of R who would like to refresh, deepen, and supplement their statistical-methodical knowledge. 
In this course, you will learn to understand key aspects of inferential statistics and to use R/RStudio for selected statistical tests and models.
Course notes, practices and suggested solutions, data files and R code are provided in a cloud.
Please note: If the class takes place on premises, there are PCs available in the course room with R/RStudio installed. If the class is online, you need to have R/RStudio installed on your computer. There are no resources available on the course days to install R/RStudio or to solve technical problems.


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