Module 5

Key topics

• Clustering
• Principal Component Analysis
• Multidimensional Scaling
• Linear Discriminant Analysis

R packages and datasets

It is assumed in all following examples of this module that the following code has been executed successfully.

packages used in this module

library(tidyverse) ## general functionality
library(palmerpenguins) ## penguins data
library(GGally) ## nice looking pairs plots
library(factoextra) ## multivariate analysis
library(vegan) ## multivariate analysis
library(ape) ## dendograms
library(MASS) ## linear discriminant analysis
library(ggfortify) ## plotting
library(pheatmap) ## plotting
library(ade4) ## plotting

datasets used in this module

base_url <- "https://raw.githubusercontent.com/STATS-UOA/databunker/master/data/"

1. palmerpenguins::penguins

data(penguins, package = "palmerpenguins")

2. ants

ants <- read_csv(paste(base_url, "pitfalls.csv", sep = ""))

3. north_island

north_island <- read_csv(paste(base_url, "north_islands_distances.csv", sep = "")) %>% 
  column_to_rownames(var = "...1")

4. ekman¹¹

ekman <- read_csv(paste(base_url, "ekman.csv", sep = ""))

5. eurodist

data("eurodist", package = "datasets")

6. HairEyeColor¹²

data("HairEyeColor", package = "datasets")

7. diabetes

diabetes <- read_csv(paste(base_url, "diabetes.csv", sep = ""))

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11. Source: Dimensions of color vision↩

12. Source: Graphical display of two-way contingency tables and Graphical methods for categorical data↩