Setup

Installing and Using Required Packages

Throughout this tutorial, we’ll use a few essential R packages to manipulate data, run models, and create plots.
Below are the core packages, what they do, and how to install them.

Packages we’ll use:

ggplot2 – For plotting (e.g., scatterplots, regression lines)
dplyr – For data wrangling (filtering, mutating, summarizing, etc.)
gridExtra – To combine multiple plots into one figure
stats – Comes with base R and used for regression (lm())
pacman – Simplifies package management in R broom (optional) – Makes model summaries easier to work with

# install.packages(c("ggplot2", "dplyr", "gridExtra", "pacman", "broom"))

Loading Packages

library(ggplot2)
library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:igraph':
## 
##     as_data_frame, groups, union

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(gridExtra)

## 
## Attaching package: 'gridExtra'

## The following object is masked from 'package:dplyr':
## 
##     combine

# Optional if using tidy model outputs:
# library(broom)

Difference Between install.packages() and library()

install.packages(“dplyr”) downloads and installs the package — you only need to do this once per computer.
library(dplyr) loads the package into your R session — you need to run this each time you use it.

Session Information

It’s always good practice to include your session info at the end of your analysis. This gives a snapshot of:

Your R version and system details
All the packages that were loaded
The versions of those packages

This is especially useful when:
- You’re debugging errors
- You’re submitting assignments
- You’re collaborating with others

Why include this?

Sometimes code behaves differently depending on the version of a package or even the version of R itself. Including your session info makes your work reproducible and easier to troubleshoot.

Base R version (simple)

This function comes with R and gives you basic session details.

sessionInfo()

## R version 4.5.1 (2025-06-13)
## Platform: aarch64-apple-darwin20
## Running under: macOS Sequoia 15.7.4
## 
## Matrix products: default
## BLAS:   /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib 
## LAPACK: /Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.12.1
## 
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## time zone: America/Los_Angeles
## tzcode source: internal
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] gridExtra_2.3 dplyr_1.1.4   ggplot2_3.5.2 igraph_2.2.1  bnlearn_5.1   cobalt_4.6.0  bookdown_0.46
## 
## loaded via a namespace (and not attached):
##  [1] crayon_1.5.3       vctrs_0.6.5        cli_3.6.5          knitr_1.50         rlang_1.1.6        xfun_0.52         
##  [7] generics_0.1.4     jsonlite_2.0.0     glue_1.8.0         htmltools_0.5.8.1  sass_0.4.10        scales_1.4.0      
## [13] rmarkdown_2.29     grid_4.5.1         jquerylib_0.1.4    evaluate_1.0.4     tibble_3.3.0       fastmap_1.2.0     
## [19] yaml_2.3.10        lifecycle_1.0.4    compiler_4.5.1     RColorBrewer_1.1-3 pkgconfig_2.0.3    rstudioapi_0.17.1 
## [25] farver_2.1.2       digest_0.6.37      R6_2.6.1           tidyselect_1.2.1   parallel_4.5.1     pillar_1.11.0     
## [31] magrittr_2.0.3     bslib_0.9.0        withr_3.0.2        tools_4.5.1        gtable_0.3.6       cachem_1.1.0