Analysis of My Fortnite Data

With an introduction to Quarto

Author

Introduction

My data involves statistics for many different players during Fortnite games. Each row is a different players’ results for that specific round. The columns make up different categories to judge the performance.

Research Question

Do sober players place tend to get more kills than high players?

I will be using the fortnite data set from above, specifically the Mental State and Eliminations Column. The rows each represent a different players’ stats, so I will be able to filter the players based on whether they were sober or not along with the eliminations each had. I prepare to answer this question with a visualization, and I did not see any reasons for any filters or subgroups since I can easily filter out the different Mental States.

Proof:

As you can see from the two visualizations, there is not significant evidence to prove that sober players get more kills than high players. In the bar chart, you see a slightly higher bar for sober players. In the box plot, you can barely see a difference once the outliers are removed. The second box plot is the data with the outliers and technically there are two players with above average eliminations. However, based on my findings, I was unable to determine if sober players get more eliminations than high players.

--- title: "Analysis of My Fortnite Data" # Name of your HTML output subtitle: "With an introduction to Quarto" author: "CT" # Author name editor: visual toc: true # Generates an automatic table of contents. format: # Options related to formatting. html: # Options related to HTML output. code-tools: TRUE # Allow the code tools option showing in the output. embed-resources: TRUE # Embeds all components into a single HTML file. execute: # Options related to the execution of code chunks. warning: FALSE # FALSE: Code chunk sarnings are hidden by default. message: FALSE # FALSE: Code chunk messages are hidden by default. echo: FALSE # FALSE: Show no code in the output. --- ## Introduction My data involves statistics for many different players during Fortnite games. Each row is a different players' results for that specific round. The columns make up different categories to judge the performance. ```{r} #| include: false #| label: setup library(tidyverse) # For all the tidy things, yo library(skimr) # For better summary stats ``` ```{r} #| label: load data #| message: FALSE fortnite <- read_csv("https://myxavier-my.sharepoint.com/:x:/g/personal/temmingc_xavier_edu/EagPrrd_UBxIpVQ890rEn9QBi3KQEDq3DHZ0ft-I9QP09w?download=1") ``` ## Research Question Do sober players place tend to get more kills than high players? I will be using the fortnite data set from above, specifically the Mental State and Eliminations Column. The rows each represent a different players' stats, so I will be able to filter the players based on whether they were sober or not along with the eliminations each had. I prepare to answer this question with a visualization, and I did not see any reasons for any filters or subgroups since I can easily filter out the different Mental States. Proof: ```{r} #| label: prrof #| echo: FALSE boxplot(fortnite$Eliminations~fortnite$`Mental State`, outline = FALSE, col = 'red', main = 'High vs Sober Eliminations', xlab = 'Mental State', ylab = 'Eliminations') boxplot(fortnite$Eliminations~fortnite$`Mental State`, col = 'red', main = 'High vs Sober Eliminations', xlab = 'Mental State', ylab = 'Eliminations') fortnite %>% ggplot(aes(x = `Mental State`, y = Eliminations)) + geom_bar(stat = 'summary', fun = mean) + labs(title = 'High vs Sober Eliminations') ``` As you can see from the two visualizations, there is not significant evidence to prove that sober players get more kills than high players. In the bar chart, you see a slightly higher bar for sober players. In the box plot, you can barely see a difference once the outliers are removed. The second box plot is the data with the outliers and technically there are two players with above average eliminations. However, based on my findings, I was unable to determine if sober players get more eliminations than high players.