README.md

In graebnerc/DataScienceExercises: Exercises for introductions to R

Exercises for using R for data science

This package contains exercises for getting started with the programming language R. They were designed to align with the courses I am teaching at the Europa-University Flensburg (such as this one), but the material they cover is most likely part of many introductions to R.

You can install this package via

remotes::install_github(repo = "graebnerc/DataScienceExercises")

Then you can complete exercises by calling the following command:

learnr::run_tutorial(
  name = "name_of_exercise_sheet", 
  package = "DataScienceExercises", 
  shiny_args=list("launch.browser"=TRUE))

The first exercise collection, for instance, is called "Basics" and is called by:

learnr::run_tutorial(
  name = "Basics", 
  package = "DataScienceExercises", 
  shiny_args=list("launch.browser"=TRUE))

Here is a list of the exercises currently available:

| Exercise code | Description | |:-------------------|:---------------------------------------------------------------------------------------| | Basics | Exercises on how to conduct basic tasks in R | | Functions | Exercises on how to define your own functions | | ObjectTypes1 | Exercises on how to handle basic object types | | ObjectTypes2 | Exercises on how to use advanced object types, such as data frames, tibbles or factors | | Visualization1 | Building plots using ggplot2 | | ProjectOrga | How to set up an R project and use the here function | | ProjectOrga | How to import data, especially csv files using `data.table::fread() | | RMarkdown | An older version that contains some exercises on R Markdown | | Quarto | A newer version that contains some exercises on Quarto | | Wrangling1 | The basics of manipulating and reshaping data frames | | Wrangling2 | More exercises on making data wider or longer | | LinearRegression1 | Basics of linear regression models | | LinearRegression2 | More advanced applications for linear regression models | | Sampling | Simulating random processes and conduct Monte Carlo simulations | | Models | Multiple choice questions on the theory of models | | | |

For bug reports and feedback please use the Github issue tracker.

graebnerc/DataScienceExercises documentation built on April 11, 2025, 7:57 p.m.