Welcome !

Welcome to this R course! In this course I will teach you the workflow from raw data to your very first analyses in R. When I was a beginner myself, I tried a lot of courses like this, but there were two points, which I think slowed down my learning process, I do want to make different with this course:

  • The courses taught way too much unnecessary stuff for the beginning. It does not matter to know several variations of a command for example, the intuition is way more important.

This course was originally a tutorial for my juniors at my university and I asked myself the question: What do they need to know, to conduct data analyses themselves with R? Well, they have to get an intuition of the workflow. So I decided to design a course, that instead of showing unnecessary variations of functions aim to show how to analyse a question of interest.

  • The courses were not reproducible! That is not the directly the fault of the courses. There are tools to make R scripts reproducible, however they are not beginner friendly, so the authors of those courses are facing a trade-off: Teaching unnecessary complicated stuff at to beginners, or to leave it out and make the course not reproducible.

This course is different! In this course, you can download R-scripts and load them directly on your own device and follow the course by executing the codes for yourself to have the original experience of working with R.

About this Course

Prerequisities

  • R and RStudio. You should download the most current version of R and RStudio. How to do that easily is described here.

What is R and RStudio ?

R is a programming language specifically developed for statistical analysis. RStudio is the standard graphical interface to work with R.

Why R ?

  • Free of cost and open-source
  • Functionalities for all steps of research process from Data Collection to Data Analysis
  • Programming language specifically developed for statistical analysis
  • Very active Community:
  • e.g. R community on StackOverflow
  • e.g. #rstats on twitter

What expects you and what not

In this course you will learn:

  • To get familiar with R and its basic language
  • Core commands from the tidyverse package
  • Data Manipulation
  • An efficient Workflow
  • A brief introduction into basic Data Analysis and Exploratory Data Analysis.

You will not learn:

  • Advanced R usage (Webscraping, Quantitative Text Analysis etc…)

Overview of the course structure:

1. The R environment

  • Basic Functionality (Calculations, Vectors, Matrices, Lists)
  • Object classes
  • Accessing, Subsetting and Naming Objects

2. Data Manipulation

  • Pipelines or Piping
  • The tidyverse - Dplyr
  • Loading and Storing Data
  • Ordering your Data: Renaming, Re-Ordering, Subsetting and Selecting
  • Transforming Variables
  • Merging Data
  • Missing Values

3. Exploratory Data Analysis/Descriptives

  • Standard Descriptive Statistics (Mean, Median, SD,….)
  • Contingency Tables
  • Correlations
  • Working with EDA packages

4. Data Visualization

  • The Tidyverse - ggplot 2
  • Constructing Plots
  • Plotting anything

5. Data Analysis

  • Linear Regression

  • Model Fit

  • Hypothesis Testing with R

  • Multivariate Regression

  • Categorical Variables

6. R Programming

  • For loops
  • Apply function
  • Functions

7. Further Explanations Data Analysis

  • Probability Theory
  • Regression Diagnostics

About Me

My name is Okan and I am Political Scientist by training and currently work as a Consultant for Data and AI. My job is to enable my clients to use data science to make their lifes easier and thus better. As mentioned this course started as an Introduction for my graduate students to R and I hope it will continue to teach R to everyone, who is as enthusiastic about data as my students were back then!

Be part of this Course! Please report errors, bugs and problems with the code. If you have any ideas how to improve this course please contact me on GitHub or via E-Mail. In general, let us stay in touch, follow me on GitHub and LinkedIn and if you like this course share your experience and recommend it to others!