Introduction

Last updated on 2025-06-24 | Edit this page

Overview

Questions

  • What is this all about?

Objectives

  • Explain the general structure of this introductory course
  • Explain how to submit “homework” assignments

Introduction

This is the accompanying website to the Empra Differentielle Psychologie of Heidelberg University. It is authored and used by Sven Lesche. This course aims to cover:

  • Some R basics and how to structure code
  • Getting a first glimpse of data
  • Cleaning data
  • Running some analysis

Lesson Structure

The entire course is organized in short “Episodes” intended to take around 10-15mins to read and around 5-10mins to complete the challenges below. You will complete approximately one episode per week. At the end of each episode, you will upload a script containing the solutions to the challenges. The file format should be: lessonnumber_solutions_name_surname.R. Upload the script containing your solutions to a HeiBox folder and share that folder with me.

A word about Chat-GPT

Chat-GPT is an amazing tool that makes it much easier to just try something out. Importantly, it can take a lot of work off your hands, especially early on in your learning process. Most of the challenges here can just be solved by plugging them into a LLM like Chat-GPT. I encourage you to first try to find a solution yourself. You will learn a lot more by failing yourself first and continuing to try.

Nonetheless, sometimes it may be necessary to ask Chat-GPT or google a solution. In real data analysis, this is done a lot! Nobody knows anything. However, the most important thing for now is that you understand the code you write. Thus, if you use Chat-GPT, make it explain to you why this code works and what it is doing or ask it for hints instead of the solution.

Accompanying Material

This course relies heavily on R for Data Science (2e), which can be treated as an accompanying textbook.

Questions & Support

This is the first version of the new course material. If you have any questions or notice any inconsistencies / opportunities for improvement, feel free to reach out to to me via mail or Slack. If you feel comfortable using GitHub, also feel free to submit an issue.

Some opportunities for improvement are:

  • Is the material sufficiently explained? Can you follow?
  • Are the exercises too difficult / not enough to practice material learned in an episode?
  • Are you missing any information to complete following episodes?
  • Is there information missing or information that you do not require?
  • Are there any typos / wrong examples?
  • Whatever else comes to mind.

Feel free to reach out to me via any of the channels with your feedback. I will try to implement it as soon as possible. Thank you for your help in making this course better for coming students!

Key Points

  • Follow the structured outline to learn R basics and data analysis
  • Submit weekly scripts following the specified format
  • Contact me via mail or Slack for any queries