Statistics with R

Preface

This a little ebook-esque thing I’m working on which explains how to do some statistics stuff in R, how to present data, etc. Expect more content to be added in the future.

Currently, all the demonstrations use R and tidyverse code, and most of the information comes from content I learned in my university biostatistics course, with some other information being pulled from other online materials I’ve used in the past or MOOCs I’ve taken on my own.

The organization and structure of this site may look a little busy right now, but I’m working on flushing out all the information at the moment, and it will be reworked in the future and made more accessible.

Assumptions

This site assumes you have some rudimentary knowledge of R/programming: what variables are, how functions work, etc. All the pages will also assume you have the tidyverse package loaded. Any other packages that are used will be specified in the page itself.

If you don’t have tidyverse installed, you can install it as such:

install.packages('tidyverse')

Once you have it installed, load it into your workspace by running this command, and you’ll see the following output. tidyverse loads in all the other packages mentioned there, but most importantly, it includes:

• ggplot2, our plotting library of choice
• tibble, a way to represent tabular data in R
• dplyr, which contains utility functions to manipulate data

library(tidyverse)

── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──

✔ ggplot2 3.4.0     ✔ purrr   0.3.5
✔ tibble  3.1.7     ✔ dplyr   1.0.9
✔ tidyr   1.2.0     ✔ stringr 1.4.1
✔ readr   2.1.2     ✔ forcats 0.5.1

── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()

Accessing sample data

This website uses tons of different datasets, all of which are available at https://justsharan.xyz/stats/datasets/*. So for example, the anorexia data used for the paired t-test page can be loaded in as such:

anorexia <- read_csv('https://justsharan.xyz/stats/datasets/anorexia.csv')
head(anorexia) # just for demonstration purposes

# A tibble: 6 × 2
  Prior  Post
  <dbl> <dbl>
1  83.8  95.2
2  83.3  94.3
3  86    91.5
4  82.5  91.9
5  86.7 100. 
6  79.6  76.7