Mini-Hackathon5_answersheet.Rmd

---
layout: tutorial
title: 'Mini-Hackathon 5: Times-Series (Part II)'
author: ""
output: pdf_document
editor_options: 
  chunk_output_type: console
---
  
```{r setup, include=FALSE}
## include this at top of your RMarkdown file for pretty output
## make sure to have the printr package installed: install.packages('printr')
knitr::opts_chunk$set(echo = TRUE)
library(printr)
library(rmarkdown)
```

Mini-Hackathons are performed and submitted in pairs of two. 
You must hand in your assignment on Canvas the next week before **Tuesday Midnight**.

Use this RMarkdown template on the canvas page for this mini-hackathon to complete your hackathon.
When you are finished, knit the file into a pdf with the knit button in the toolbar (or using Ctrl+Shift+K).
For this you need to have the `knitr` and `printr` packages installed, and all your code needs to work (see the R course companion for more instructions).
**If you cannot knit the `.Rmd` file, there is probably an error in your R code, therefore add `eval=FALSE` to the code chunk: `{r, eval = FALSE}`, so you are still able to knit and upload the file.**

# This Mini-Hackathon
This mini-hackathon builds upon **all** tutorials of this course.
For this hackathon, you're therefore strongly required to revisit the tutorials of the last five weeks.
If you aim to conduct additional analyses in R, we of course encourage this.
Nevertheless, it is important to not do additional analysis just for the sake of running more code chunks. 
For that reason, please provide a justification for these additional analyses.

Also, we recommend to use parameters for RMarkdown codeblocks, in particular the `cache = TRUE` parameter for codeblocks that take long to compute (e.g., downloading data from AmCAT). 
A brief explanation of some usefull parameters to make a `.Rmd` file pretty is given in the [the first tutorial](https://github.com/MarikenvdVelden/Replication-Hackathons/blob/main/Intro-to-rmd-and-data-retrieval.md).
Additionally, you can use [this cheat sheet](https://rstudio.com/wp-content/uploads/2015/02/rmarkdown-cheatsheet.pdf).

Important to take into account is that this week we will build upon codes of last weeks.  

### Hackathon Challenges
#### Challenge 1
 _Based on the literature in week 1 -- 6 of this course, investigate initial support for a "simple" research question that could be answered using times-series data. This question should have the structure of does variable X lead to more/ less in variable Y._
_Please describe the research question and elaborate on the data, including the data structure you need (e.g. which  level of aggregation), in order to answer the question._

#### Challenge 2
_Create a data set using a **tidy script** with your X, Y, and date variable._

#### Challenge 3
_Develop an infographic to visualize a meaningful relationship between your X and Y variable based on your data using `ggplot2`. Try to make the infographic as informative and appealing as possible._

### Challenge 4
_What does your infographic demonstrate? Interpret the infographic in light of your research question._

### Challenge 4
_To answer your question, run a correlation and interpret the value. Reflect on your research design and describe the limitations._