Claudius Graebner-Radkowitsch graebnerc

## # Skript zu Tag 3 - Wiederholungsfragen Data Prep
The notes made on the questions that you posed during day 3 on the content from day 2.

## # Skript zu Tag 3 - Visualisierung
Hier findet sich das Skript zur Entwicklung der beiden Beispielabbildung, die wir im Kurs am 15. Juli 2024 entwickelt haben, sowie den weiteren Visualisiserungsnotizen.

## # Skript zu Tag 2
Hier sind alle Notizen und Aufgabenlösungen zu Tag 2 (8. Juli 2024).

## # Skript zu Tag 1
Hier sind alle Notizen und Aufgabenlösungen zu Tag 1 (1. Juli 2024).

## LinearRegression.R
library(tibble)
library(ggplot2)
library(moderndive)

# 1. Implement linear regression-----------------
# Make a shortcut to the data:
beer_data <- as_tibble(DataScienceExercises::beer)
head(beer_data)

# Conduct the linear regression:

## #MCS-Tutorial exercises
Solutions to the exercises that are mentioned in the tutorial on Monte Carlo Simulations.

## # Sampling
Code used during the lecture on sampling.

## #T9: Solution
The Netlify version can be found at: https://quarto-ex-solution.netlify.app/

## DesasterMarkdown.qmd
---
title: "What a desaster!"
author: "Claudius"
date: '2024-05-07'
format: pdf
---

# Packages used
```{r}
library(tidyverse)

## # Data Preparation: solutions
Solutions for the exercises in the session on data preparation.
	library(tibble)
	library(ggplot2)
	library(moderndive)

	# 1. Implement linear regression-----------------
	# Make a shortcut to the data:
	beer_data <- as_tibble(DataScienceExercises::beer)
	head(beer_data)

	# Conduct the linear regression:
	---
	title: "What a desaster!"
	author: "Claudius"
	date: '2024-05-07'
	format: pdf
	---

	# Packages used
	```{r}
	library(tidyverse)